An fMRI-based neurologic signature of physical pain

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'.

Spatiotemporal integration of contextual and sensory information within the cortical hierarchy in human pain experience

Pain is not a mere reflection of noxious input. Rather, it is constructed through the dynamic integration of current predictions with incoming sensory input. However, the temporal dynamics of the behavioral and neural processes underpinning this integration remain elusive. In the current study involving 59 human participants, we identified a series of brain mediators that integrated cue-induced expectations with noxious inputs into ongoing pain predictions using a semicircular scale designed to capture rating trajectories. Temporal mediation analysis revealed that during the early-to-mid stages of integration, the frontoparietal and dorsal attention network regions, such as the lateral prefrontal, premotor, and parietal cortex, mediated the cue effects. Conversely, during the mid-to-late stages of integration, the somatomotor network regions mediated the effects of stimulus intensity, suggesting that the integration occurs along the cortical hierarchy from the association to sensorimotor brain systems. Our findings advance the understanding of how the brain integrates contextual and sensory information into pain experience over time.

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 two 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 role 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.

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.

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.

A novel cortical biomarker signature predicts individual pain sensitivity

Importance

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

Objective

The present study aimed to undertake analytical validation of a sensorimotor cortical biomarker signature for pain consisting of two measures: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME).

Design

In this cohort study (recruitment period: November 2020-October 2022), participants experienced a model of prolonged temporomandibular pain with outcomes collected over 30 days. Electroencephalography (EEG) 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 1-30.

Setting

Data collection occurred at a single centre: Neuroscience Research Australia.

Participants

We enrolled 159 healthy participants (through notices placed online and at universities across Australia), aged 18-44 with no history of chronic pain, neurological or psychiatric condition. 150 participants completed the protocol.

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

We determined the predictive accuracy of the PAF/CME biomarker signature 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

The final sample consisted of 66 females and 84 males with a mean age of 25.1 ± 6.2. 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[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-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.

Key Points

Question: Can individuals be accurately classified as high or low pain sensitive based on two features of cortical activity: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME)?Findings: In a cohort study of 150 healthy participants, the performance of a logistic regression model was outstanding in a training set (n=100) and excellent in a test set (n=50), with the combination of slower PAF and CME depression predicting higher pain. Results were reproduced across a range of methodological parameters.Meaning: A novel cortical biomarker can accurately distinguish high and low pain sensitive individuals, and may predict the transition from acute to chronic pain.

Functional connectivity in complex regional pain syndrome: A bicentric study

Brain imaging studies in complex regional pain syndrome (CRPS) have found mixed evidence for functional and structural changes in CRPS. In this cross-sectional study, we evaluated two patient cohorts from different centers and examined functional connectivity (rsFC) in 51 CRPS patients and 50 matched controls. rsFC was compared in predefined ROI pairs, but also in non-hypothesis driven analyses. Resting state (rs)fMRI changes in default mode network (DMN) and the degree rank order disruption index (kD) were additionally evaluated. Finally, imaging parameters were correlated with clinical severity and somatosensory function. Among predefined pairs, we found only weakly to moderately lower functional connectivity between the right nucleus accumbens and bilateral ventromedial prefrontal cortex in the infra-slow oscillations (ISO) band. The unconstrained ROI-to-ROI analysis revealed lower rsFC between the periaqueductal gray matter (PAG) and left anterior insula, and higher rsFC between the right sensorimotor thalamus and nucleus accumbens. In the correlation analysis, pain was positively associated with insulo-prefrontal rsFC, whereas sensorimotor thalamo-cortical rsFC was positively associated with tactile spatial resolution of the affected side. In contrast to previous reports, we found no group differences for kD or rsFC in the DMN, but detected overall lower data quality in patients. In summary, while some of the previous results were not replicated despite the larger sample size, novel findings from two independent cohorts point to potential down-regulated antinociceptive modulation by the PAG and increased connectivity within the reward system as pathophysiological mechanisms in CRPS. However, in light of the detected systematic differences in data quality between patients and healthy subjects, validity of rsFC abnormalities in CRPS should be carefully scrutinized in future replication studies.

Investigating neuroepigenetic alterations in chronic low back pain with positron emission tomography

ABSTRACT

Epigenetics has gained considerable interest as potential mediators of molecular alterations that could underlie the prolonged sensitization of nociceptors, neurons, and glia in response to various environmental stimuli. Histone acetylation and deacetylation, key processes in modulating chromatin, influence gene expression; elevated histone acetylation enhances transcriptional activity, whereas decreased acetylation leads to DNA condensation and gene repression. Altered levels of histone deacetylase (HDAC) have been detected in various animal pain models, and HDAC inhibitors have demonstrated analgesic effects in these models, indicating HDACs' involvement in chronic pain pathways. However, animal studies have predominantly examined epigenetic modulation within the spinal cord after pain induction, which may not fully reflect the complexity of chronic pain in humans. Moreover, methodological limitations have previously impeded an in-depth study of epigenetic changes in the human brain. In this study, we employed [ 11 C]Martinostat, an HDAC-selective radiotracer, positron emission tomography to assess HDAC availability in the brains of 23 patients with chronic low back pain (cLBP) and 11 age-matched and sex-matched controls. Our data revealed a significant reduction of [ 11 C]Martinostat binding in several brain regions associated with pain processing in patients with cLBP relative to controls, highlighting the promising potential of targeting HDAC modulation as a therapeutic strategy for cLBP.

A cellular mechanism contributing to pain-induced analgesia

ABSTRACT

The anterior cingulate cortex (ACC) plays a crucial role in the perception of pain. It is consistently activated by noxious stimuli and its hyperactivity in chronic pain indicates plasticity in the local neuronal network. However, the way persistent pain effects and modifies different neuronal cell types in the ACC and how this contributes to sensory sensitization is not completely understood. This study confirms the existence of 2 primary subtypes of pyramidal neurons in layer 5 of the rostral, agranular ACC, which we could classify as intratelencephalic (IT) and cortico-subcortical (SC) projecting neurons, similar to other cortical brain areas. Through retrograde labeling, whole-cell patch-clamp recording, and morphological analysis, we thoroughly characterized their different electrophysiological and morphological properties. When examining the effects of peripheral inflammatory pain on these neuronal subtypes, we observed time-dependent plastic changes in excitability. During the acute phase, both subtypes exhibited reduced excitability, which normalized to pre-inflammatory levels after day 7. Daily conditioning with nociceptive stimuli during this period induced an increase in excitability specifically in SC neurons, which was correlated with a decrease in mechanical sensitization. Subsequent inhibition of the activity of SC neurons projecting to the periaqueductal gray with in vivo chemogenetics, resulted in reinstatement of the hypersensitivity. Accordingly, it was sufficient to enhance the excitability of these neurons chemogenetically in the inflammatory pain condition to induce hypoalgesia. These findings suggest a cell type-specific effect on the descending control of nociception and a cellular mechanism for pain-induced analgesia. Furthermore, increased excitability in this neuronal population is hypoalgesic rather than hyperalgesic.

Pain-Discriminating Information Decoded From Spatiotemporal Patterns of Hemodynamic Responses Measured by fMRI in the Human Brain

Functional magnetic resonance imaging (fMRI) has been widely used in studying the neural mechanisms of pain in the human brain, primarily focusing on where in the brain pain-elicited neural activities occur (i.e., the spatial distribution of pain-related brain activities). However, the temporal dynamics of pain-elicited hemodynamic responses (HDRs) measured by fMRI may also contain information specific to pain processing but have been largely neglected. Using high temporal resolution fMRI (TR = 0.8 s) data acquired from 62 healthy participants, in the present study we aimed to test whether pain-distinguishing information could be decoded from the spatial pattern of the temporal dynamics (i.e., the spatiotemporal pattern) of HDRs elicited by painful stimuli. Specifically, the peak latency and the response duration were used to characterize the temporal dynamics of HDRs to painful laser stimuli and non-painful electric stimuli, and then were compared between the two conditions (i.e., pain and no-pain) using a voxel-wise univariate analysis and a multivariate pattern analysis. Furthermore, we also tested whether the two temporal characteristics of pain-elicited HDRs and their spatial patterns were associated with pain-related behaviors. We found that the spatial patterns of HDR peak latency and response duration could successfully discriminate pain from no-pain. Interestingly, we also observed that the Pain Vigilance and Awareness Questionnaire (PVAQ) scores were correlated with the average response duration in bilateral insula and secondary somatosensory cortex (S2) and could also be predicted from the across-voxel spatial patterns of response durations in the middle cingulate cortex and middle frontal gyrus only during painful condition but not during non-painful condition. These findings indicate that the spatiotemporal pattern of pain-elicited HDRs may contain pain-specific information and highlight the importance of studying the neural mechanisms of pain by taking advantage of the high sensitivity of fMRI to both spatial and temporal information of brain responses.

Hearing Function Moderates Age-Related Differences in Brain Morphometry in the HCP Aging Cohort

There are well-established relationships between aging and neurodegenerative changes, and between aging and hearing loss. The goal of this study was to determine how structural brain aging is influenced by hearing loss. Human Connectome Project Aging data were analyzed, including T1-weighted Magnetic Resonance Imaging (MRI) and Words in noise (WIN) thresholds (n = 623). Freesurfer extracted gray and white matter volume, and cortical thickness, area, and curvature. Linear regression models targeted (1) interactions between age and WIN threshold and (2) correlations with WIN threshold adjusted for age, both corrected for false discovery rate (pFDR < 0.05). WIN threshold moderated age-related increase in volume in bilateral inferior lateral ventricles, with a higher threshold associated with increased age-related ventricle expansion. Age-related differences in the occipital cortex also increased with higher WIN thresholds. When controlling for age, high WIN threshold was correlated with reduced cortical thickness in Heschl's gyrus, calcarine sulcus, and other sensory regions, and reduced temporal lobe white matter. Older volunteers with poorer hearing and cognitive scores had the lowest volume in left parahippocampal white matter. These results suggest that better hearing is associated with reduced age-related differences in medial temporal lobe, while better hearing at any age is associated with greater cortical tissue in auditory and other sensory regions. Future longitudinal studies are needed to assess the causal nature of these relationships, but these results indicate interventions that preserve or protect hearing function may combat some neurodegenerative changes in aging.

Pediatric Neural Changes to Physical and Emotional Pain After Intensive Interdisciplinary Pain Treatment: A Pilot Study

OBJECTIVE

Brain areas activated during pain can contribute to enhancing or reducing the pain experience, showing a potential connection between chronic pain and the neural response to pain in adolescents and youth.

METHODS

This study examined changes in brain activation associated with experiencing physical pain and observing physical and emotional pain in others by using functional magnetic resonance imaging (fMRI) before and after intensive interdisciplinary pain treatment (IIPT). Eighteen youths (age 14 to 18) with widespread chronic pain completed fMRI testing before and after IIPT to assess changes in brain activation in response to physical and emotional pain.

RESULTS

Broadly, brain activation changes were observed in frontal, somatosensory, and limbic regions. These changes may suggest improvements in descending pain modulation via thalamus and caudate, and the different pattern of brain activation after treatment suggests potentially better discrimination between physical and emotional pain. Brain activation changes were also correlated with improvements in clinical outcomes of catastrophizing (reduced activation in right caudate, right mid-cingulate, and postcentral gyrus) and pain-related disability (increased activation in precentral gyrus, left hippocampus, right middle occipital cortex, and left superior frontal gyrus).

DISCUSSION

These changes could indicate that reduced brain protective responses to pain were associated with treatment-related improvements. This pilot study highlights the need for larger trials designed to better understand the brain mechanisms involved in pediatric widespread pain treatment.

Advances and challenges in neuroimaging-based pain biomarkers

Identifying neural biomarkers of pain has long been a central theme in pain neuroscience. Here, we review the state-of-the-art candidates for neural biomarkers of acute and chronic pain. We classify these potential neural biomarkers into five categories based on the nature of their target variables, including neural biomarkers of (1) within-individual perception, (2) between-individual sensitivity, and (3) discriminability for acute pain, as well as (4) assessment and (5) prospective neural biomarkers for chronic pain. For each category, we provide a synthesized review of candidate biomarkers developed using neuroimaging techniques including functional magnetic resonance imaging (fMRI), structural magnetic resonance imaging (sMRI), and electroencephalography (EEG). We also discuss the conceptual and practical challenges in developing neural biomarkers of pain. Addressing these challenges, optimal biomarkers of pain can be developed to deepen our understanding of how the brain represents pain and ultimately help alleviate patients' suffering and improve their well-being.

Closed-loop neural interfaces for pain: Where do we stand?

Advances in closed-loop neural interfaces and neuromodulation have offered a potentially effective and non-addictive treatment for chronic pain. These interfaces link neural sensors with device outputs to provide temporally precise stimulation. We discuss challenges and trends of state-of-the-art neural interfaces for treating pain in animal models and human pilot trials.

Clinical pain management: Current practice and recent innovations in research

Chronic pain affects one in five adults. It is not only a major cause of disability for individual patients but also a driver of costs for entire healthcare systems. Treatment of pain remains a challenge, and the use of opioids has further led to a concurrent opioid epidemic. In this review, we discuss current standard treatment options for chronic pain, including pharmacological, behavioral, and interventional treatments. In addition, we review ongoing research in different areas that will potentially unlock new therapies.

Neural mechanisms underlying placebo and nocebo effects in tonic muscle pain

Pain is a highly subjective and multidimensional experience, significantly influenced by various psychological factors. Placebo analgesia and nocebo hyperalgesia exemplify this influence, where inert treatments result in pain relief or exacerbation, respectively. While extensive research has elucidated the psychological and neural mechanisms behind these effects, most studies have focused on transient pain stimuli. To explore these mechanisms in the context of tonic pain, we conducted a study using a 15-minute tonic muscle pain induction procedure, where hypertonic saline was infused into the left masseter of healthy participants. We collected real-time Visual Analogue Scale (VAS) scores and functional magnetic resonance imaging (fMRI) data during the induction of placebo analgesia and nocebo hyperalgesia via conditioned learning. Our findings revealed that placebo analgesia was more pronounced and lasted longer than nocebo hyperalgesia. Real-time pain ratings correlated significantly with neural activity in several brain regions. Notably, the putamen was implicated in both effects, while the caudate and other regions were differentially involved in placebo and nocebo effects. These findings confirm that the tonic muscle pain paradigm can be used to investigate the mechanisms of placebo and nocebo effects and indicate that placebo analgesia and nocebo hyperalgesia may have more distinct than common neural bases.

Pain Catastrophizing and Functional Activation During Occlusion in TMD Patients-An Interventional Study

In temporomandibular disorder (TMD), the effects of standard interventions such as using an occlusal splint and its impact on pain relief and pain catastrophizing are poorly understood. Earlier work pointed to a crucial role of insula activation with changes in pain relief by occlusal splint treatment. We performed a functional imaging study using specially developed splint systems to allow for a placebo-controlled longitudinal design. Using functional MRI we examined 20 TMD patients during repetitive occlusal movements at baseline and over the course of splint therapy and also collected self-reported pain catastrophizing. For balancing performance between baseline and after intervention we used occlusion force measures in an individualized fMRI-splint system. Splint therapy lasted for approximately 7 weeks with one group selected by randomization wearing a palatine placebo splint over the first 3 weeks (delayed start; 11 individuals). As expected, fMRI activation in areas involved in pain processing (insula, primary and secondary somatosensory cortex) decreased with intervention. At baseline a positive correlation between activation of the left anterior insula and pain catastrophizing was present. Both parameters decreased over intervention while associations were primarily observable for patients with rather mild TMD.

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 in a paradigm that manipulates both the mean value and the precision of cues within-person. Forty-five participants observed cues-presented as ratings from 10 previous participants-with varying cue means, variances (precision), and skewness across trials. Participants reported expectations regarding the painfulness of thermal stimuli or the visual contrast of flickering checkerboards. Subsequently, similar cues were each followed by a visual or noxious thermal stimulus. While perceptions assimilated to expected values in both modalities, cues' precision mainly affected visual ratings. Furthermore, behavioral and computational models revealed that expectations were biased towards extreme values in both modalities, and towards low-pain cues specifically. fMRI analysis revealed that the cues affected systems related to higher-level affective and cognitive processes-including assimilation to the cue mean in a neuromarker of endogenous contributions to pain and in the nucleus accumbens, and activity consistent with aversive prediction-error-like encoding in the periaqueductal gray during pain perception-but not systems related to early perceptual processing. Our findings suggest that predictive processing theories should be combined with mechanisms such as selective attention to better fit empirical findings, and that expectation generation and its perceptual effects are mostly modality-specific and operate on higher-level processes rather than early perception.

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.

Mental state decoders: game-changers or wishful thinking?

Decoding mental and perceptual states using fMRI has become increasingly popular over the past two decades, with numerous highly-cited studies published in high-profile journals. Nevertheless, what have we learned from these decoders? In this opinion, we argue that fMRI-based decoders are not neurophysiologically informative and are not, and likely cannot be, applicable to real-world decision-making. The former point stems from the fact that decoding models cannot disentangle neural mechanisms from their epiphenomena. The latter point stems from both logical and ethical constraints. Constructing decoders requires precious time and resources that should instead be directed toward scientific endeavors more likely to yield meaningful scientific progress.

The expectations humans have of a pleasurable sensation asymmetrically shape neuronal responses and subjective experiences to hot sauce

Expectations shape our perception, profoundly influencing how we interpret the world. Positive expectations about sensory stimuli can alleviate distress and reduce pain (e.g., placebo effect), while negative expectations may heighten anxiety and exacerbate pain (e.g., nocebo effect). To investigate the impact of the (an)hedonic aspect of expectations on subjective experiences, we measured neurobehavioral responses to the taste of hot sauce among participants with heterogeneous taste preferences. By identifying participants who "liked" versus those who strongly "disliked" spicy flavors and by providing contextual cues about the spiciness of the sauce to be tasted, we dissociated the effects of positive and negative expectations from sensory stimuli (i.e., visual and gustatory stimuli), which were the same across all participants. Our results indicate that positive expectations lead to modulations in the intensity of subjective experience. These modulations were accompanied by increased activity in brain regions previously linked to information integration and the placebo effect, including the anterior insula, dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex, as well as a predefined "pleasure signature." In contrast, negative expectations decreased hedonic experience and increased neural activity in the previously validated "Neurological Pain Signature" network. These findings demonstrate that hedonic aspects of one's expectations asymmetrically shape how the brain processes sensory input and associated behavioral reports of one's subjective experiences of intensity, pleasure, and pain. Our results suggest a dissociable impact of hedonic information: positive expectations facilitate higher-level information integration and reward processing, while negative expectations prime lower-level nociceptive and affective processes. This study demonstrates the powerful role of hedonic expectations in shaping subjective reality and suggests potential avenues for consumer and therapeutic interventions targeting expectation-driven neural processes.

An approach to the detection of pain from autonomic and cortical correlates

OBJECTIVE

To assess the value of combining brain and autonomic measures to discriminate the subjective perception of pain from other sensory-cognitive activations.

METHODS

20 healthy individuals received 2 types of tonic painful stimulation delivered to the hand: electrical stimuli and immersion in 10 Celsius degree (°C) water, which were contrasted with non-painful immersion in 15 °C water, and stressful cognitive testing. High-density electroencephalography (EEG) and autonomic measures (pupillary, electrodermal and cardiovascular) were continuously recorded, and the accuracy of pain detection based on combinations of electrophysiological features was assessed using machine learning procedures.

RESULTS

Painful stimuli induced a significant decrease in contralateral EEG alpha power. Cardiac, electrodermal and pupillary reactivities occurred in both painful and stressful conditions. Classification models, trained on leave-one-out cross-validation folds, showed low accuracy (61-73%) of cortical and autonomic features taken independently, while their combination significantly improved accuracy to 93% in individual reports.

CONCLUSIONS

Changes in cortical oscillations reflecting somatosensory salience and autonomic changes reflecting arousal can be triggered by many activating signals other than pain; conversely, the simultaneous occurrence of somatosensory activation plus strong autonomic arousal has great probability of reflecting pain uniquely.

SIGNIFICANCE

Combining changes in cortical and autonomic reactivities appears critical to derive accurate indexes of acute pain perception.

Why does mobile payment promote purchases? Revisiting the pain of paying, and understanding the implicit pleasure via selective attention

The past years have witnessed a phenomenal growth of the mobile payment market, but how mobile payment affects purchase behavior receives less attention from academics. Recent studies suggested that lower pain of paying may not fully clarify the relationship between mobile payment and increased purchases (i.e., mobile payment effect). The current research first introduced price level in Study 1 and demonstrated that the pain of paying served as an underlying mechanism only in the high-price condition rather than the low-price condition. As such, Study 2 was conducted in a low-price context to address the uncovered mechanisms. We propose a new concept of "pleasure of payment" that is defined as an implicit and consumption-related hedonic response based on the cue theory of consumption. By tracking spontaneous attention to positive attributes (i.e., benefits) of products, Study 2 demonstrated this implicit pleasure as a psychological mechanism for the mobile payment effect when the pain of paying was not at play. These findings have important implications for mobile payment in research and practice by identifying price level as a boundary condition for the role of pain of paying and understanding the positive downstream consequences of mobile payment usage on consumer psychology.

Trait reward sensitivity modulates connectivity with the temporoparietal junction and Anterior Insula during strategic decision making

Many decisions happen in social contexts such as negotiations, yet little is understood about how people balance fairness versus selfishness. Past investigations found that activation in brain areas involved in executive function and reward processing was associated with people offering less with no threat of rejection from their partner, compared to offering more when there was a threat of rejection. However, it remains unclear how trait reward sensitivity may modulate activation and connectivity patterns in these situations. To address this gap, we used task-based fMRI to examine the relation between reward sensitivity and the neural correlates of bargaining choices. Participants (N = 54) completed the Sensitivity to Punishment (SP)/Sensitivity to Reward (SR) Questionnaire and the Behavioral Inhibition System/Behavioral Activation System scales. Participants performed the Ultimatum and Dictator Games as proposers and exhibited strategic decisions by being fair when there was a threat of rejection, but being selfish when there was not a threat of rejection. We found that strategic decisions evoked activation in the Inferior Frontal Gyrus (IFG) and the Anterior Insula (AI). Next, we found elevated IFG connectivity with the Temporoparietal junction (TPJ) during strategic decisions. Finally, we explored whether trait reward sensitivity modulated brain responses while making strategic decisions. We found that people who scored lower in reward sensitivity made less strategic choices when they exhibited higher AI-Angular Gyrus connectivity. Taken together, our results demonstrate how trait reward sensitivity modulates neural responses to strategic decisions, potentially underscoring the importance of this factor within social and decision neuroscience.

Functional magnetic resonance imaging studies in bipolar disorder in resting state: A coordinates-based meta-analysis

Exploring changes in the intrinsic activity of the brain in people with bipolar disorder (BD) is necessary. However, the findings have not yet led to consistent conclusions. In this regard, this paper aims to extract more obvious differential brain areas and neuroimaging markers, for the purpose of providing assistance for early clinical diagnosis and subsequent treatment. We conducted a meta-analysis of whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) studies using seed-based d-mapping software that examined differences in amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo) between patients with BD and healthy controls (HCs). Seed-based d-Mapping (formerly Signed Differential Mapping) with Permutation of Subject Images, or SDM-PSI, is a statistical technique for meta-analyzing studies of differences in brain activity or structure. A total of 16 articles involving 1112 individuals were included in this study for meta-analysis. This paper confidently analyzes the correlation between the clinical scales HAMD, HAMA, and YMRS, and the area of difference. We found significant changes that increased activation in the anterior connective and left lens nucleus, the nucleus of the shell, and BA 48 in BD patients compared with HC (P < 0.05, uncorrected), as well as a significant correlation between HAMD and the left superior frontal gyrus (after FWE correction P < 0.05). Therefore, basal ganglia and frontal cortex may have important significance in the pathogenesis and pathological basis of BD, making it an important issue to be attached importance to.

Neuromodulation for Neuropathic Pain Syndromes

OBJECTIVE

This article reviews the principles, applications, and emerging trends of neuromodulation as a therapeutic approach for managing painful neuropathic diseases. By parsing evidence for possible mechanisms of action and clinical trial outcomes for various diseases, this article focuses on five common therapy modalities: cutaneous, peripheral nerve, spinal cord, and brain stimulation, and intrathecal drug delivery.

LATEST DEVELOPMENTS

Recent advances in both invasive and noninvasive neuromodulation for pain have introduced personalized and closed-loop techniques, integrating real-time feedback mechanisms and combining therapies to improve physical and psychosocial function. Novel stimulation waveforms may influence distinct neural tissues to rectify pathologic pain signaling.

ESSENTIAL POINTS

With appropriate patient selection, peripheral nerve stimulation or epidural stimulation of the spinal cord can provide enduring relief for a variety of chronic pain syndromes. Newer technology using high frequencies, unique waveforms, or closed-loop stimulation may have selective advantages, but our current understanding of therapy mechanisms is very poor. For certain diagnoses and patients who meet clinical criteria, neuromodulation can provide profound, long-lasting relief that significantly improves quality of life. While many therapies are supported by data from large clinical trials, there is a risk of bias as most clinical studies were funded by device manufacturers or insurance companies, which increases the importance of real-world data analysis. Emerging methods like invasive or noninvasive brain stimulation may help us dissect basic mechanisms of pain processing and hold promise for personalized therapies for refractory pain syndromes. Finally, intrathecal delivery of drugs directly to segments of the spinal cord can also modify pain signaling to provide therapy for severe pain syndromes.

Psychopathy and medial frontal cortex: A systematic review reveals predominantly null relationships

Theories have posited that psychopathy is caused by dysfunction in the medial frontal cortex, including ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), and dorsomedial prefrontal cortex (dmPFC). Recent reviews have questioned the reproducibility of neuroimaging findings within this field. We conducted a systematic review to describe the consistency of magnetic resonance imaging (MRI) findings according to anatomical subregion (vmPFC, ACC, dmPFC), experimental task, psychopathy assessment, study power, and peak coordinates of significant effects. Searches of PsycInfo and MEDLINE databases produced 77 functional and 24 structural MRI studies that analyzed the medial frontal cortex in relation to psychopathy in adult samples. Findings were predominantly null (85.4 % of 1573 tests across the three medial frontal regions). Studies with higher power observed null effects at marginally lower rates. Finally, peak coordinates of significant effects were widely dispersed. The evidence failed to support theories positing the medial frontal cortex as a consistent neural correlate of psychopathy. Theory and methods in the field should be revised to account for predominantly null neuroimaging findings.

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.

Low-intensity focused ultrasound to the insula differentially modulates the heartbeat-evoked potential: A proof-of-concept study

OBJECTIVE

The heartbeat evoked potential (HEP) is a brain response time-locked to the heartbeat and a potential marker of interoceptive processing that may be generated in the insula and dorsal anterior cingulate cortex (dACC). Low-intensity focused ultrasound (LIFU) can selectively modulate sub-regions of the insula and dACC to better understand their contributions to the HEP.

METHODS

Healthy participants (n = 16) received stereotaxically targeted LIFU to the anterior insula (AI), posterior insula (PI), dACC, or Sham at rest during continuous electroencephalography (EEG) and electrocardiography (ECG) recording on separate days. Primary outcome was HEP amplitudes. Relationships between LIFU pressure and HEP changes and effects of LIFU on heart rate and heart rate variability (HRV) were also explored.

RESULTS

Relative to sham, LIFU to the PI, but not AI or dACC, decreased HEP amplitudes; PI effects were partially explained by increased LIFU pressure. LIFU did not affect heart rate or HRV.

CONCLUSIONS

These results demonstrate the ability to modulate HEP amplitudes via non-invasive targeting of key interoceptive brain regions.

SIGNIFICANCE

Our findings have implications for the causal role of these areas in bottom-up heart-brain communication that could guide future work investigating the HEP as a marker of interoceptive processing in healthy and clinical populations.

Neural processing of audiovisual and painful analogue trauma and its relationship with subsequent audiovisual and pain intrusions

Background: Posttraumatic stress disorder and medically unexplained pain frequently co-occur. While pain is common during traumatic events, the processing of pain during trauma and its relation to audiovisual and pain intrusions is poorly understood.Objective: Here we investigate neural activations during painful analogue trauma, focusing on areas that have been related to threat and pain processing, and how they predict intrusion formation. We also examine the moderating role of cumulative lifetime adversity.Methods: Sixty-five healthy women were assessed using functional magnetic resonance imaging. An analogue trauma was induced by an adaptation of the trauma-film paradigm extended by painful electrical stimulation in a 2 (film: aversive, neutral) x 2 (pain: pain, no-pain) design, followed by 7-day audiovisual and pain intrusion assessment using event-based ecological momentary assessment. Intrusions were fitted with Bayesian multilevel regression and a hurdle lognormal distribution.Results: Conjunction analysis confirmed a wide network including anterior insula (AI) and dorsal anterior cingulate cortex (dACC) being active both, during aversive films and pain. Pain resulted in activation in areas amongst posterior insula and deactivation in a network around ventromedial prefrontal cortex (VMPFC). Higher AI and dACC activity during aversive>neutral film predicted greater audiovisual intrusion probability over time and predicted greater audiovisual intrusion frequency particularly for participants with high lifetime adversity. Lower AI, dACC, hippocampus, and VMPFC activity during pain>no-pain predicted greater pain intrusion probability particularly for participants with high lifetime adversity. Weak regulatory VMPFC activation was associated with both increased audiovisual and pain intrusion frequency.Conclusions: Enhanced AI and dACC processing during aversive films, poor pain vs. no-pain discrimination in AI and dACC, as well as weak regulatory VMPFC processing may be driving factors for intrusion formation, particularly in combination with high lifetime adversity. Results shed light on a potential path for the etiology of PTSD and medically unexplained pain.

A structural MRI marker predicts individual differences in impulsivity and classifies patients with behavioral-variant frontotemporal dementia from matched controls

Impulsivity and higher preference for sooner over later rewards (i.e., delay discounting) are transdiagnostic markers of many psychiatric and neurodegenerative disorders. Yet, their neurobiological basis is still debated. Here, we aimed at 1) identifying a structural MRI signature of delay discounting in healthy adults, and 2) validating it in patients with behavioral variant frontotemporal dementia (bvFTD)-a neurodegenerative disease characterized by high impulsivity. We used a machine-learning algorithm to predict individual differences in delay discounting rates based on whole-brain grey matter density maps in healthy male adults (Study 1, N=117). This resulted in a cross-validated prediction-outcome correlation of r=0.35 (p=0.0028). We tested the validity of this brain signature in an independent sample of 166 healthy adults (Study 2) and its clinical relevance in 24 bvFTD patients and 18 matched controls (Study 3). In Study 2, responses of the brain signature did not correlate significantly with discounting rates, but in both Studies 1 and 2, they correlated with psychometric measures of trait urgency-a measure of impulsivity. In Study 3, brain-based predictions correlated with discounting rates, separated bvFTD patients from controls with 81% accuracy, and were associated with the severity of disinhibition among patients. Our results suggest a new structural brain pattern-the Structural Impulsivity Signature (SIS)-which predicts individual differences in impulsivity from whole-brain structure, albeit with small-to-moderate effect sizes. It provides a new brain target that can be tested in future studies to assess its diagnostic value in bvFTD and other neurodegenerative and psychiatric conditions characterized by high impulsivity.

Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine

Personalized pain medicine aims to tailor pain treatment strategies for the specific needs and characteristics of an individual patient, holding the potential for improving treatment outcomes, reducing side effects, and enhancing patient satisfaction. Despite existing pain markers and treatments, challenges remain in understanding, detecting, and treating complex pain conditions. Here, we review recent engineering efforts in developing various sensors and devices for addressing challenges in the personalized treatment of pain. We summarize the basics of pain pathology and introduce various sensors and devices for pain monitoring, assessment, and relief. We also discuss advancements taking advantage of rapidly developing medical artificial intelligence (AI), such as AI-based analgesia devices, wearable sensors, and healthcare systems. We believe that these innovative technologies may lead to more precise and responsive personalized medicine, greatly improved patient quality of life, increased efficiency of medical systems, and reducing the incidence of addiction and substance use disorders.

Synaptic sensitization in the anterior cingulate cortex sustains the consciousness of pain via synchronized oscillating electromagnetic waves

A recent report showed that experiencing pain requires not only activities in the brain, but also the generation of electric fields in a defined area of the anterior cingulate cortex (ACC). The present manuscript presents evidence that electromagnetic (EM) waves are also necessary. Action potentials (APs) encoding information about an injury stimulate thousands synapses on pyramidal neurons within the ACC resulting in the generation of synchronized oscillating (EM) waves and the activation of NMDA receptors. The latter induces a long-term potentiation (LTP) in the pyramidal dendrites that is necessary to experience both neuropathic and visceral pain. The LTP sensitizes transmission across the synapses that sustains the duration of the waves and the pain, EM waves containing information about the injury travel throughout the brain and studies using transcranial stimulation indicate that they can induce NMDA-mediated LTP in distant neuronal circuits. What is ultimately experienced as pain depends on the almost instantaneous integration of information from numerous neuronal centers, such as the amygdala, that are widely separated in the brain. These centers also generate EM waves and I propose that the EM waves from these centers interact to rapidly adjust the intensity of the pain to accommodate past and present circumstances. Where the waves are transformed into a consciousness of pain is unknown. One possibility is the mind which, according to contemporary theories, is where conscious experiences arise. The hypothesis can be tested directly by blocking the waves from the ACC. If correct, the waves would open new avenues of research into the relationship between the brain, consciousness, and the mind.

A behavioral signature for quantifying the social value of interpersonal relationships with specific others

The idea that individuals ascribe value to social phenomena, broadly construed, is well-established. Despite the ubiquity of this concept, defining social value in the context of interpersonal relationships remains elusive. This is notable because while prominent theories of human social behavior acknowledge the role of value-based processes, they mostly emphasize the value of individual actions an agent may choose to take in a given environment. Comparatively little is known about how humans value their interpersonal relationships. To address this, we devised a method for engineering a behavioral signature of social value in several independent samples (total N = 1111). Incorporating the concept of opportunity cost from economics and data-driven quantitative methods, we derived this signature by sourcing and weighting a range of social behaviors based on how likely individuals are to prioritize them in the face of limited resources. We examined how strongly the signature was expressed in self-reported social behaviors with specific relationship partners (a parent, close friend, and acquaintance). Social value scores track with other aspects of these relationships (e.g., relationship quality, aversion to losing relationship partners), are predictive of decision preferences on a range of tasks, and display good psychometric properties. These results provide greater mechanistic specificity in delineating human value-based behavior in social contexts and help parse the motivational relevance of the different facets that comprise interpersonal relationships.

Principles of cortical areas and their implications for neuroimaging

Cortical organization should constrain the study of how the brain performs behavior and cognition. A fundamental concept in cortical organization is that of arealization: that the cortex is parceled into discrete areas. In part one of this report, we review how non-human animal studies have illuminated principles of cortical arealization by revealing: (1) what defines a cortical area, (2) how cortical areas are formed, (3) how cortical areas interact with one another, and (4) what "computations" or "functions" areas perform. In part two, we discuss how these principles apply to neuroimaging research. In doing so, we highlight several examples where the commonly accepted interpretation of neuroimaging observations requires assumptions that violate the principles of arealization, including nonstationary areas that move on short time scales, large-scale gradients as organizing features, and cortical areas with singular functionality that perfectly map psychological constructs. Our belief is that principles of neurobiology should strongly guide the nature of computational explanations.

Contributions of neuroimaging in central poststroke pain: a review

BACKGROUND

 Central neuropathic poststroke pain (CNPSP) affects up to 12% of patients with stroke in general and up to 18% of patients with sensory deficits. This pain syndrome is often incapacitating and refractory to treatment. Brain computed tomography and magnetic resonance imaging (MRI) are widely used methods in the evaluation of CNPSP.

OBJECTIVE

 The present study aims to review the role of neuroimaging methods in CNPSP.

METHODS

 We performed a literature review of the main clinical aspects of CNPSP and the contribution of neuroimaging methods to study its pathophysiology, commonly damaged brain sites, and possible differential diagnoses. Lastly, we briefly mention how neuroimaging can contribute to the non-pharmacological CNPSP treatment. Additionally, we used a series of MRI from our institution to illustrate this review.

RESULTS

 Imaging has been used to explain CNPSP pathogenesis based on spinothalamic pathway damage and connectome dysfunction. Imaging locations associated with CNPSP include the brainstem (mainly the dorsolateral medulla), thalamus (especially the ventral posterolateral/ventral posteromedial nuclei), cortical areas such as the posterior insula and the parietal operculum, and, more recently, the thalamocortical white matter in the posterior limb of the internal capsule. Imaging also brings the prospect of helping search for new targets for non-pharmacological treatments for CNPSP. Other neuropathic pain causes identified by imaging include syringomyelia, multiple sclerosis, and herniated intervertebral disc.

CONCLUSION

 Imaging is a valuable tool in the complimentary evaluation of CNPSP patients in clinical and research scenarios.

Neural responses to oral administration of erythritol vs. sucrose and sucralose explain differences in subjective liking ratings

INTRODUCTION

High sugar intake is associated with many chronic diseases. However, non-caloric sweeteners (NCSs) might fail to successfully replace sucrose due to the mismatch between their rewarding sweet taste and lack of caloric content. The natural NCS erythritol has been proposed as a sugar substitute due to its satiating properties despite being non-caloric. We aimed to compare brain responses to erythritol vs. sucrose and the artificial NCS sucralose in a priori taste, homeostatic, and reward brain regions of interest (ROIs).

METHODS

We performed a within-subject, single-blind, counterbalanced fMRI study in 30 healthy men (mean ± SEM age:24.3 ± 0.8 years, BMI:22.3 ± 0.3 kg/m2). Before scanning, we individually matched the concentrations of both NCSs to the perceived sweetness intensity of a 10% sucrose solution. During scanning, participants received 1 mL sips of the individually titrated equisweet solutions of sucrose, erythritol, and sucralose, as well as water. After each sip, they rated subjective sweetness liking.

RESULTS

Liking ratings were significantly higher for sucrose and sucralose vs. erythritol (both pHolm = 0.0037); water ratings were neutral. General Linear Model (GLM) analyses of brain blood oxygen level-depended (BOLD) responses at qFDR<0.05 showed no differences between any of the sweeteners in a priori ROIs, but distinct differences were found between the individual sweeteners and water. These results were confirmed by Bayesian GLM and machine learning-based models. However, several brain response patterns mediating the differences in liking ratings between the sweeteners were found in whole-brain multivariate mediation analyses. Both subjective and neural responses showed large inter-subject variability.

CONCLUSION

We found lower liking ratings in response to oral administration of erythritol vs. sucrose and sucralose, but no differences in neural responses between any of the sweeteners in a priori ROIs. However, differences in liking ratings between erythritol vs. sucrose or sucralose are mediated by multiple whole-brain response patterns.

Dopamine has no direct causal role in the formation of treatment expectations and placebo analgesia in humans

Dopamine-based reward and learning mechanisms have been suggested to contribute to placebo effects. However, the exact role of dopaminergic neurotransmission in their generation and maintenance is still unclear. This study aimed to shed light on the causal role of dopamine in establishing positive treatment expectations, as well as on the magnitude and duration of their effect on pain. To this end, we used an established placebo analgesia paradigm in combination with 2 opposing pharmacological modulations of dopaminergic tone, i.e., the dopamine antagonist sulpiride and the dopamine precursor L-dopa which were both applied in an experimental, double-blind, randomized, placebo-controlled trial with a between-subject design in N = 168 healthy volunteers. The study medication successfully altered dopaminergic tone during the conditioning procedure. Contrary to our hypotheses, the medication did not modulate the formation of positive treatment expectation and placebo analgesia tested 1 day later. Placebo analgesia was no longer detectable on day 8 after conditioning. Using a combined frequentist and Bayesian approach, our data provide strong evidence against a direct dopaminergic influence on the generation and maintenance of placebo effects. Further exploration of the neurochemical mechanisms underlying placebo analgesia remains paramount in the quest to exploit these effects for optimal treatment outcomes. Trial registration: ClinicalTrials.gov German Clinical Trials Register, ID: DRKS00029366, https://drks.de/search/en/trial/DRKS00029366.

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.

Hacking the Predictive Mind

According to active inference, constantly running prediction engines in our brain play a large role in delivering all human experience. These predictions help deliver everything we see, hear, touch, and feel. In this paper, I pursue one apparent consequence of this increasingly well-supported view. Given the constant influence of hidden predictions on human experience, can we leverage the power of prediction in the service of human flourishing? Can we learn to hack our own predictive regimes in ways that better serve our needs and purposes? Asking this question rapidly reveals a landscape that is at once familiar and new. It is also challenging, suggesting important questions about scope and dangers while casting further doubt (as if any was needed) on old assumptions about a firm mind/body divide. I review a range of possible hacks, starting with the careful use of placebos, moving on to look at chronic pain and functional disorders, and ending with some speculations concerning the complex role of genetic influences on the predictive brain.

From Maps to Models: A Survey on the Reliability of Small Studies of Task-Based fMRI

Task-based functional magnetic resonance imaging is a powerful tool for studying brain function, but neuroimaging research produces ongoing concerns regarding small-sample studies and how to interpret them. Although it is well understood that larger samples are preferable, many situations require researchers to make judgments from small studies, including reviewing the existing literature, analyzing pilot data, or assessing subsamples. Quantitative guidance on how to make these judgments remains scarce. To address this, we leverage the Human Connectome Project's Young Adult dataset to survey various analyses-from regional activation maps to predictive models. We find that, for some classic analyses such as detecting regional activation or cluster peak location, studies with as few as 40 subjects are adequate, although this depends crucially on effect sizes. For predictive modeling, similar sizes can be adequate for detecting whether features are predictable, but at least an order of magnitude more (at least hundreds) may be required for developing consistent predictions. These results offer valuable insights for designing and interpreting fMRI studies, emphasizing the importance of considering effect size, sample size, and analysis approach when assessing the reliability of findings. We hope that this survey serves as a reference for identifying which kinds of research questions can be reliably answered with small-scale studies.

Identification of group differences in predictive anticipatory biasing of pain during uncertainty: preparing for the worst but hoping for the best

ABSTRACT

Pain anticipation during conditions of uncertainty can unveil intrinsic biases, and understanding these biases can guide pain treatment interventions. This study used machine learning and functional magnetic resonance imaging to predict anticipatory responses in a pain anticipation experiment. One hundred forty-seven participants that included healthy controls (n = 57) and individuals with current and/or past mental health diagnosis (n = 90) received cues indicating upcoming pain stimuli: 2 cues predicted high and low temperatures, while a third cue introduced uncertainty. Accurate differentiation of neural patterns associated with specific anticipatory conditions was observed, involving activation in the anterior short gyrus of the insula and the nucleus accumbens. Three distinct response profiles emerged: subjects with a negative bias towards high pain anticipation, those with a positive bias towards low pain anticipation, and individuals whose predictions during uncertainty were unbiased. These profiles remained stable over one year, were consistent across diagnosed psychopathologies, and correlated with cognitive coping styles and underlying insula anatomy. The findings suggest that individualized and stable pain anticipation occurs in uncertain conditions.

Systematic review and co-ordinate based meta-analysis to summarize the utilization of functional brain imaging in conjunction with human models of peripheral and central sensitization

BACKGROUND AND OBJECTIVE

Functional magnetic resonance imaging, in conjunction with models of peripheral and/or central sensitization, has been used to assess analgesic efficacy in healthy humans. This review aims to summarize the use of these techniques to characterize brain mechanisms of hyperalgesia/allodynia and to evaluate the efficacy of analgesics.

DATABASES AND DATA TREATMENT

Searches were performed (PubMed-Medline, Cochrane, Web of Science and Clinicaltrials.gov) to identify and review studies. A co-ordinate based meta-analysis (CBMA) was conducted to quantify neural activity that was reported across multiple independent studies in the hyperalgesic condition compared to control, using GingerALE software.

RESULTS

Of 217 publications, 30 studies met the inclusion criteria. They studied nine different models of hyperalgesia/allodynia assessed in the primary (14) or secondary hyperalgesia zone (16). Twenty-three studies focused on neural correlates of hyperalgesic conditions and showed consistent changes in the somatosensory cortex, prefrontal cortices, insular cortex, anterior cingulate cortex, thalamus and brainstem. The CBMA on 12 studies that reported activation coordinates for a contrast comparing the hyperalgesic state to control produced six activation clusters (significant at false discovery rate of 0.05) with more peaks for secondary (17.7) than primary zones (7.3). Seven studies showed modulation of brain activity by analgesics in five of the clusters but also in four additional regions.

CONCLUSIONS

This meta-analysis revealed substantial but incomplete overlap between brain areas related to neural mechanisms of hyperalgesia and those reflecting the efficacy of analgesic drugs. Studies testing in the secondary zone were more sensitive to evaluate analgesic efficacy on central sensitization at brainstem or thalamocortical levels.

SIGNIFICANCE

Experimental pain models that provide a surrogate for features of pathological pain conditions in healthy humans and functional imaging techniques are both highly valuable research tools. This review shows that when used together, they provide a wealth of information about brain activity during pain states and analgesia. These tools are promising candidates to help bridge the gap between animal and human studies, to improve translatability and provide opportunities for identification of new targets for back-translation to animal studies.

DeepComBat: A statistically motivated, hyperparameter-robust, deep learning approach to harmonization of neuroimaging data

Neuroimaging data acquired using multiple scanners or protocols are increasingly available. However, such data exhibit technical artifacts across batches which introduce confounding and decrease reproducibility. This is especially true when multi-batch data are analyzed using complex downstream models which are more likely to pick up on and implicitly incorporate batch-related information. Previously proposed image harmonization methods have sought to remove these batch effects; however, batch effects remain detectable in the data after applying these methods. We present DeepComBat, a deep learning harmonization method based on a conditional variational autoencoder and the ComBat method. DeepComBat combines the strengths of statistical and deep learning methods in order to account for the multivariate relationships between features while simultaneously relaxing strong assumptions made by previous deep learning harmonization methods. As a result, DeepComBat can perform multivariate harmonization while preserving data structure and avoiding the introduction of synthetic artifacts. We apply this method to cortical thickness measurements from a cognitive-aging cohort and show DeepComBat qualitatively and quantitatively outperforms existing methods in removing batch effects while preserving biological heterogeneity. Additionally, DeepComBat provides a new perspective for statistically motivated deep learning harmonization methods.

Dissecting shared pain representations to understand their behavioral and clinical relevance

Accounts of shared representations posit that the experience of pain and pain empathy rely on similar neural mechanisms. Experimental research employing novel analytical and methodological approaches has made significant advances in both the identification and targeted manipulation of such shared experiences and their neural underpinnings. This revealed that painful experiences can be shared on different representational levels, from pain-specific to domain-general features, such as negative affect and its regulation. In view of direct links between such representations and social behaviors such as prosocial behavior, conditions characterized by aberrant pain processing may come along with heavy impairments in the social domain, depending on the affected representational level. This has wide potential implications in light of the high prevalence of pain-related clinical conditions, their management, and the overuse of pain medication. In this review and opinion paper, we aim to chart the path toward a better understanding of the link between shared affect and prosocial behavior.

The Brain Salience Network at the Intersection of Pain and Substance use Disorders: Insights from Functional Neuroimaging Research

Purpose of Review

The brain's salience network (SN), primarily comprising the anterior insula and anterior cingulate cortex, plays a key role in detecting salient stimuli and processing physical and socioemotional pain (e.g., social rejection). Mounting evidence underscores an altered SN in the etiology and maintenance of substance use disorders (SUDs). This paper aims to synthesize recent functional neuroimaging research emphasizing the SN's involvement in SUDs and physical/socioemotional pain and explore the therapeutic prospects of targeting the SN for SUD treatment.

Recent Findings

The SN is repeatedly activated during the experience of both physical and socioemotional pain. Altered activation within the SN is associated with both SUDs and chronic pain conditions, characterized by aberrant activity and connectivity patterns as well as structural changes. Among individuals with SUDs, functional and structural alterations in the SN have been linked to abnormal salience attribution (e.g., heightened responsiveness to drug-related cues), impaired cognitive control (e.g., impulsivity), and compromised decision-making processes. The high prevalence of physical and socioemotional pain in the SUD population may further exacerbate SN alterations, thus contributing to hindered recovery progress and treatment failure. Interventions targeting the restoration of SN functioning, such as real-time functional MRI feedback, neuromodulation, and psychotherapeutic approaches, hold promise as innovative SUD treatments.

Summary

The review highlights the significance of alterations in the structure and function of the SN as potential mechanisms underlying the co-occurrence of SUDs and physical/socioemotional pain. Future work that integrates neuroimaging with other research methodologies will provide novel insights into the mechanistic role of the SN in SUDs and inform the development of next-generation treatment modalities.

Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain

Drug treatments for pain often do not outperform placebo, and a better understanding of placebo mechanisms is needed to improve treatment development and clinical practice. In a large-scale fMRI study (N = 392) with pre-registered analyses, we tested whether placebo analgesic treatment modulates nociceptive processes, and whether its effects generalize from conditioned to unconditioned pain modalities. Placebo treatment caused robust analgesia in conditioned thermal pain that generalized to unconditioned mechanical pain. However, placebo did not decrease pain-related fMRI activity in brain measures linked to nociceptive pain, including the Neurologic Pain Signature (NPS) and spinothalamic pathway regions, with strong support for null effects in Bayes Factor analyses. In addition, surprisingly, placebo increased activity in some spinothalamic regions for unconditioned mechanical pain. In contrast, placebo reduced activity in a neuromarker associated with higher-level contributions to pain, the Stimulus Intensity Independent Pain Signature (SIIPS), and affected activity in brain regions related to motivation and value, in both pain modalities. Individual differences in behavioral analgesia were correlated with neural changes in both modalities. Our results indicate that cognitive and affective processes primarily drive placebo analgesia, and show the potential of neuromarkers for separating treatment influences on nociception from influences on evaluative processes.

An externally validated resting-state brain connectivity signature of pain-related learning

Pain can be conceptualized as a precision signal for reinforcement learning in the brain and alterations in these processes are a hallmark of chronic pain conditions. Investigating individual differences in pain-related learning therefore holds important clinical and translational relevance. Here, we developed and externally validated a novel resting-state brain connectivity-based predictive model of pain-related learning. The pre-registered external validation indicates that the proposed model explains 8-12% of the inter-individual variance in pain-related learning. Model predictions are driven by connections of the amygdala, posterior insula, sensorimotor, frontoparietal, and cerebellar regions, outlining a network commonly described in aversive learning and pain. We propose the resulting model as a robust and highly accessible biomarker candidate for clinical and translational pain research, with promising implications for personalized treatment approaches and with a high potential to advance our understanding of the neural mechanisms of pain-related learning.