bioRxiv Science⌕ Search

Biology subjects

Wager, T. D.

Publications and source records attributed to Wager, T. D..

At least 19 recordsLinked to original sources

Hippocampus mediates conceptual generalization of pain modulation

Pain is strongly influenced by expectations and learning from previous experience, such as in classical conditioning. Conditioned responses and expectations can generalize to perceptually and conceptually related cues, but how generalization influences pain experience and the neurobiological processing of pain remains unclear. We used fMRI and multilevel mediation analyses to address this question. Thirty-six human participants first learned to associate two visual cues from distinct conceptual categories (e.g., animals vs. vehicles) with high or low levels of heat pain. In a subsequent phase, they were presented with novel cues (images, drawings, or words) not previously paired with pain, but which shared the conceptual category of the initial pain-predictive cues. Participants who developed explicit expectations during learning reported greater pain in response to stimuli conceptually related to high- vs. low-pain cues (generalization stimuli), demonstrating generalization of cue influences on pain. This effect was mediated by increased pain-related activity to generalization stimuli in the hippocampus, which correlated with individual differences in cue-evoked expectations. A broader network, including areas of the default mode network and striatum, also contributed to conceptual generalization of pain modulation, while threat-related regions such as the amygdala responded to generalization stimuli but did not mediate effects on pain ratings. These findings extend our understanding of expectancy-driven pain modulation by showing how conceptual processes can influence pain and its neurobiological substrates, offering new insight into placebo effects and maladaptive learning in chronic pain.

neuroscience↗

The State of Motion: Demographic and representational consequences of motion-based exclusion in fMRI

Large-scale neuroimaging datasets are increasingly used to map relationships between brain structure, function, and behavior across the human lifespan. Routinely, analyses exclude participants who moved too much during imaging. While this decision is framed as quality control, it is increasingly recognized that head motion is not randomly distributed across individuals within a study, and so motion-based exclusion may preferentially remove people with particular characteristics relevant to the scientific goals of the study. Here we survey head motion and how it relates to participant characteristics across six large, publicly available datasets spanning nearly the entire human lifespan, namely the Human Connectome Project (HCP) Young Adult, HCP in Development, HCP in Aging, Adolescent Brain Cognitive DevelopmentSM Study, UK Biobank, and Spatial Topology project. These six datasets comprise more than 50,000 unique participants and 300,000 scans. We further benchmark our findings against motion distributions aggregated by MRIQC across more than 1.5 million scans. Under commonly applied strict exclusion thresholds, large fractions of participants would be removed (exceeding 80 % in the UK Biobank task data), and these removals were demographically structured, disproportionately excluding younger and older participants, those with higher BMI, and those with motion-associated clinical conditions. Respiratory pseudo-motion inflated estimates of head motion in adult cohorts, and applying notch filtering to remove respiratory frequencies from these estimates meaningfully reduced exclusion rates. Exclusion also carried downstream consequences. Strict thresholds reduced statistical power, inflated study costs, and altered the apparent predictability of behavioral phenotypes by removing a non-random, behaviorally distinct subgroup. These findings demonstrate that motion exclusion thresholds are not neutral quality-control decisions but structured selection mechanisms that reshape the composition of neuroimaging samples. We recommend that studies report the demographic characteristics of excluded participants, prefer data-driven censoring methods over fixed motion cutoffs, and clarify the target population while considering appropriate weighting techniques.

neuroscience↗

Temporal Interference Stimulation of the Motor Cortex Produces Frequency-Dependent Analgesia

Background: Transcranial temporal interference stimulation (tTIS) is an emerging noninvasive neuromodulation approach that enables focal, frequency-specific modulation of deep brain regions, offering a novel method for investigating therapeutic mechanisms underlying brain and mental health disorders. Pain is a key target because it is a feature of multiple disorders and is increasingly understood to depend on brain circuits. Here, we tested the effects of tTIS on bilateral evoked pain, capitalizing on converging evidence from human and animal studies indicating that the primary motor cortex (M1) contains body-wide inter-effector regions and has descending projections to regions implicated in nociceptive, motivational, and autonomic processing, making it a key cortical target for pain modulation. Methods: We conducted a pre-registered, triple-blind, randomized crossover study (N = 32, 160 study sessions), investigating frequency-dependent effects of tTIS applied to the left M1 on experimentally evoked thermal pain in healthy adults. We tested four stimulation frequencies (10 Hz, 20 Hz, 70 Hz, and sham) on separate days (>10,000 pain trials total). Noxious heat was applied to both the right and left forearms using individually calibrated temperatures both pre- and post-stimulation. Results: Active tTIS produced significant analgesia at all stimulation frequencies (10 Hz, 20 Hz, and 70 Hz) relative to sham (Cohens d = 0.46-0.82, all p < 0.05). 10 Hz produced the greatest reduction (d = 0.82), and both 10 Hz and 20 Hz produced more analgesia than 70 Hz (d = 0.44 and 0.38, respectively; p < 0.05). Stimulation-related sensations were equivalent across frequencies, and participants were blind to condition. Pain reductions remained stable over a [~]40-min post-stimulation period and were bilateral, consistent with stimulation of body-wide inter-effector regions. Conclusions: These results provide the first evidence that tTIS can reliably reduce experimental pain perception in humans in a frequency-dependent manner, providing a foundation for noninvasive pain modulation with tTIS.

neuroscience↗

Cerebellar activation in human placebo analgesia: Bridging findings from mice to humans

Placebo analgesia has traditionally been explained by top-down cortical regulation of brainstem and spinal pathways. Recent circuit-level work in animal models identified a rostral anterior cingulate-pontine-cerebellar pathway that contributes to expectation-based analgesia, implicating cerebellum circuits in placebo effects1. Building on these findings, we examined pontine and cerebellar contributions within a large individual-participant meta-analysis of human neuroimaging studies of placebo analgesia2 (n = 603). We found that the effects of human pain and placebo converge in cerebellar territories embedded in higher-order cognitive3,4 and action-mode networks5. These regions exhibit placebo-induced anticipatory increases and reduced responses during painful stimulation, which correlate with the magnitude of placebo analgesia, consistent with predictive configuration of the system. Pontine responses also correlate with individual differences in placebo analgesia. In independent Human Connectome Project data (n = 820), pontine activity is functionally connected with cingulate and cerebellar regions implicated in placebo analgesia. Together, these findings support a model in which expectation effects are implemented via predictive configuration of a cortico-pontine-cerebellar system.

neuroscience↗

Precision Functional Mapping of Imagined and Experienced Pain

Imagination is a principal human capacity, enabling simulation of sensations and situations for planning, learning, and empathy. We examined neural representations of experienced and imagined pain across eight body sites using deep-phenotyping, precision functional MRI with over seven hours of scanning per participant (N = 9). Here we show, using conventional mapping, pattern classification, and representational similarity analyses, that both imagined and experienced pain activated nociceptive regions (e.g., dorsoposterior insula) and non-nociceptive regions (e.g., premotor areas). However, imagined pain did not reliably reactivate body site-selective nociceptive patterns in any region. Instead, imagined and experienced pain shared multivariate representations across widespread cortical and subcortical regions, particularly transmodal cortical areas including dorsomedial and lateral prefrontal cortex, hippocampus, and thalamus. These findings suggest that imagination generates distributed pain-like activity while preserving a neural distinction from experienced pain. This distinction may explain the difficulty of vividly imagining pain and underlie its role in empathy, planning, and pain vulnerability.

neuroscience↗

Meta-analytic evidence for distinct neural correlates of conditioned vs. verbally induced placebo analgesia

Placebo analgesia demonstrates that belief and expectation can significantly alter pain, even without active treatment. Placebo analgesia can be induced through verbal suggestion, classical conditioning, or their combination, though the role of conditioned neural responses above and beyond effects of verbal instructions remains unclear. We conducted a systematic meta-analysis of individual participant data from 16 within-participant placebo neuroimaging studies (n = 409), employing univariate and multivariate analyses to identify shared and distinct mechanisms of placebo analgesia induced by suggestions alone versus suggestions combined with conditioning. Both techniques increased activity during pain in the dorsolateral prefrontal and inferior parietal cortices and decreased activation in the insula, putamen, and primary sensory areas. Adding conditioning enhanced engagement of regions associated with context representation and pain modulation (e.g., dorsolateral/dorsomedial prefrontal cortices) and decreases in nociceptive regions (e.g., primary sensory and insular areas). Conditioning also strengthened the association between analgesia and nociceptive activity, as reflected in the Neurologic Pain Signature. Combining conditioning with instructions yielded greater analgesia, mediated by increased ventromedial prefrontal and dorsal caudate activity, alongside decreased sensory-nociceptive and cerebellar activity. These findings suggest the two strategies rely on partially distinct mechanisms, which could be combined to optimize placebo analgesias clinical application.

neuroscience↗

The functional neurobiology of negative affective traits across regions, networks, signatures, and a machine learning multiverse

Understanding the neural basis of negative affective traits like neuroticism remains a critical challenge across psychology, neuroscience, and psychiatry. Here, we investigate which level of brain organization--regions, networks, or validated whole-brain machine-learning signatures--best explains negative affective traits in a community sample of 458 adults performing the two most widely used affective fMRI tasks, viewing emotional faces and scenes. Neuroticism could not be predicted from brain activity, with Bayesian evidence against all theory-guided neural measures. However, preregistered whole-brain models successfully decoded vulnerability to stress, a lower-level facet of neuroticism, with results replicating in a hold-out sample. The neural stress vulnerability pattern demonstrated good psychometric properties and indicated that negative affective traits are best represented by distributed whole-brain patterns related to domain-general stimulation rather than localized activity. Together with results from a comprehensive multiverse analysis across 14 traits and 1,176 models-- available for exploration in an online app--the findings speak against simplistic neurobiological theories of negative affective traits, highlight a striking gap between predicting individual differences (r<.35) and within-person emotional states (r=.88), and underscore the importance of aligning psychological constructs with neural measures at the appropriate level of granularity.

neuroscience↗

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

Human social interactions rely on the ability to reflect on ones own and others internal states and traits--a process known as mentalizing. Impaired or altered 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=390) to train and validate fMRI brain signatures that predict i) mentalizing about the self, ii) mentalizing about another person, and iii) both types of mentalizing. 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. The classifier trained across both types of mentalizing showed 98% predictive accuracy and separated (mental) attributional from factual inferences. Classifier patterns revealed better self/other separation in healthy adults compared to individuals with schizophrenia and with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving trait-based 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 candidate neuromarkers of social-cognitive processes in different contexts and clinical conditions. Author NoteThis work was funded by a Starting Grant from the European Research Council (ERC, 101041087) to LKo, a German Academic Exchange Service (DAAD) doctoral grant and a Network of European Neuroscience Schools (NENS) exchange fellowship to DA, an R01 grant from the U.S. National Institutes of Mental Health (R01MH125414-01) to JAH and DAS, a Junior Leader Fellowship from "la Caixa" Foundation (LCF/BQ/PR22/11920017) to PFC, a Consolidator Grant from the European Research Council (ERC, 648082) to LKr, R37, R01 support from the U.S. National Institutes of Mental Health (R37MH076136 to TDW, MH116026 to TDW and L. Chang [PI], R01EB026549 to TDW and M. Lindquist [MPIs]), an NIMH grant (P50MH094258-01A1) to R. Adolphs, and a CIC Brain and Mental Health Chair from the Neurodis foundation to AT. LvdM acknowledges a European Science Foundation EURYI grant (044035001) that funded her doctoral studies (PI: A. Aleman). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. The funders had no role in study design, data analysis, manuscript preparation, or publication decisions.

neuroscience↗

Convergent and selective representations of pain, appetitive processes, aversive processes, and cognitive control in the insula

Regions that respond to multiple types of information ("convergence zones") are crucial for the brain to generate coherent experiences and behaviors. The insular cortex, known for its functional diversity, has been hypothesized to be a key convergence hub, yet empirical evidence identifying how and where convergence occurs is incomplete. To address this gap, we analyzed functional convergence across four key task domains--somatic pain, non-somatic appetitive processes, aversive processes, and cognitive control--in a large-scale Bayesian mega-analysis of fMRI data (N=540, systematically sampled from 36 studies). Bayes Factor analyses identified both convergent zones responding to multiple domains and selective zones responding to single domains. Results revealed a hierarchical convergence architecture, with a multi-domain convergence zone in bilateral dorsal anterior insula surrounded by zones showing progressively increasing convergence. Functional decoding and coactivation analyses further support the insulas role as a convergence hub, while cytoarchitectonic and neurotransmitter profiling characterizes the potential neuroanatomical underpinnings subserving convergent and domain-selective function. Overall, our results demonstrate a structured functional topography in the insula that bridges specialized and convergent processing, providing a potential neural basis for how diverse information streams combine into unified subjective experiences.

neuroscience↗

Unintended bias in the pursuit of collinearity solutions in fMRI analysis

In task functional magnetic resonance imaging (fMRI), collinearity between task regressors in time series models may impact power. When collinearity is identified after data collection, researchers often modify the model in an effort to reduce collinearity. However, some model adjustments are suboptimal and may introduce bias into parameter estimates. Although relevant to many task-fMRI studies, we highlight these issues using the Monetary Incentive Delay (MID) task data from the Adolescent Brain Cognitive Development (ABCD(R)) study. We introduce a procedure to more directly quantify the impact of collinearity on task-relevant measures: a contrast-based variance inflation factor (cVIF). We also show that collinearity reduction strategies--such as omitting regressors for specific task components, using impulse regressors for extended activations, and ignoring response time variability--can bias contrast estimates. Finally, we present a "Saturated" model that includes all task components, including response times, aiming to reduce these biases while maintaining comparable levels of collinearity, as assessed by cVIF.

neuroscience↗

Image Processing in the Acute to Chronic Pain Signatures (A2CPS) Project

The Acute to Chronic Pain Signatures (A2CPS) project is a large-scale, multi-site initiative aimed at identifying biomarkers and biosignatures that predict the transition from acute to chronic pain. The project is collecting multimodal, longitudinal data from over 2,500 individuals at risk for developing chronic pain after surgery. Here we describe the neuroimaging component of A2CPS, including the acquisition protocols, processing pipelines, and contents of the initial data release. The imaging protocol includes structural, diffusion, resting-state and task-based functional magnetic resonance imaging (MRI) data. Data are collected across multiple clinical sites using different scanner manufacturers, with attention to protocol harmonization and quality control. The processing pipeline integrates several established neuroimaging tools to extract potential biomarkers, including measures of brain structure, connectivity, and pain-related neural signatures. The first data release includes pre-surgical imaging data for 595 participants, with high quality ratings across modalities (98.7% of sMRI, 99.8% of dMRI, and 94.6% of fMRI images were rated as acceptable or better). Initial analyses demonstrate expected relationships between brain-derived measures and clinical variables, such as associations between brain age and psychological factors. This dataset represents a valuable resource for both pain research and neuroimaging methods development, with future releases planned to include additional participants and expanded analysis pipelines and processed data derivatives.

neuroscience↗

Common and distinct neural correlates of social interaction perception and theory of mind

Social interaction perception and theory of mind (ToM) frequently co-occur, but their commonalities and distinctions at behavioral and neural levels remain unclear. Participants (N = 231) provided moment-by-moment ratings of four text and four audio narratives on social interactions and ToM engagement, which were reliable (split-half r = .98 and .92, respectively) but only modestly correlated (r = .32). In a second sample (N = 90), we analyzed the co-variation between social interaction and ToM ratings and fMRI activity during text and audio narratives. Social interaction and ToM activity maps generalized across modalities (spatial r = .83 and .57, respectively), both with significant, overlapping clusters in canonical mentalizing regions (FDR q < .01). ToM uniquely engaged the lateral occipitotemporal cortex, left anterior intraparietal sulcus, and right premotor cortex. These results suggest that perceiving social interactions automatically involves mentalizing, and ToM additionally engages brain regions for action understanding and executive functions.

neuroscience↗

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.

neuroscience↗

EEG-based analysis of intrinsic brain network function in chronic pain: Insights from a comprehensive multi-data set study

Chronic pain is associated with alterations in brain function. A better understanding of these alterations might help to develop new approaches for the diagnosis, prediction, and treatment of chronic pain. Here, we analyzed associations between chronic pain and alterations of intrinsic brain network function using resting-state electroencephalography. We included data from 537 people with chronic pain obtained from various research groups worldwide. We found strong evidence for associations between pain intensity and intrinsic brain network connectivity, but the replicability of these associations in independent data was mostly low. However, a mega-analysis revealed associations of chronic pain with salience-somatomotor network connectivity at theta frequencies and with more complex patterns of intrinsic brain network connectivity. These findings provide novel insights into brain network function in chronic pain. Moreover, they highlight the need for collaborative multi-center studies, which can be guided by the present approach to promote replicability and consistency of findings.

neuroscience↗

A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks

Cognitive neuroscience has advanced significantly due to the availability of openly shared datasets. Large sample sizes, large amounts of data per person, and diversity in tasks and data types are all desirable, but are difficult to achieve in a single dataset. Here, we present an open dataset with N = 101 participants and 6 hours of scanning per participant, with 6 multifaceted cognitive tasks including 2 hours of naturalistic movie viewing. This datasets combination of ample sample size, extensive data per participant, more than 600 iso hours worth of data, and a wide range of experimental conditions -- including cognitive, affective, social, and somatic/interoceptive tasks -- positions it uniquely for probing important questions in cognitive neuroscience.

neuroscience↗

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

Placebo analgesia is a replicable and well-studied phenomenon, yet it remains unclear to what degree it includes modulation of nociceptive processes. Some studies find effects consistent with nociceptive effects, but meta-analyses show that these effects are often small. We analyzed placebo analgesia in a large fMRI study (N = 392), including placebo effects on brain responses to noxious stimuli. Placebo treatment caused robust analgesia in both conditioned thermal and unconditioned mechanical pain. Placebo did not decrease fMRI activity in nociceptive pain regions, including the Neurologic Pain Signature (NPS) and pre-registered spinothalamic pathway regions, with strong support from Bayes Factor analyses. However, placebo treatment affected activity in pre-registered analyses of a second neuromarker, the Stimulus Intensity Independent Pain Signature (SIIPS), and several associated a priori brain regions related to motivation and value, in both thermal and mechanical pain. Individual differences in behavioral analgesia were correlated with neural changes in both thermal and mechanical pain. Our results indicate that processes related to affective and cognitive aspects of pain primarily drive placebo analgesia.

neuroscience↗

Brain Representations of Affective Valence and Intensity in Sustained Pleasure and Pain

Pleasure and pain are two opposites that compete and influence each other, implying the existence of brain systems that integrate them to generate modality-general affective experiences. Here, we examined the brains general affective codes (i.e., affective valence and intensity) across sustained pleasure and pain through an fMRI experiment (n = 58). We found that the distinct sub-populations of voxels within the ventromedial and lateral prefrontal cortices, the orbitofrontal cortex, the anterior insula, and the amygdala were involved in decoding affective valence versus intensity, which was replicated in an independent test dataset (n = 62). The affective valence and intensity models were connected to distinct large-scale brain networks--the intensity model to the ventral attention network and the valence model to the limbic and default mode networks. Overall, this study identified the brain representations of affective valence and intensity across pleasure and pain, promoting the systems-level understanding of human affective experiences.

neuroscience↗

Deconstructing the brain bases of emotion regulation: A systems-identification approach using Bayes factors

Cognitive reappraisal is fundamental to cognitive therapies and everyday emotion regulation. Analyses using Bayes factors and an axiomatic systems-identification approach identified four reappraisal-related components encompassing distributed neural activity patterns across two independent fMRI studies (n=182 and n=176): (1) An anterior prefrontal system selectively involved in cognitive reappraisal; (2) A fronto-parietal-insular system engaged by both reappraisal and emotion generation, demonstrating a general role in appraisal; (3) A largely subcortical system activated during negative emotion generation but unaffected by reappraisal, including amygdala, hypothalamus, and periaqueductal gray; and (4) a posterior cortical system of negative emotion-related regions down-regulated by reappraisal. These systems covaried with individual differences in reappraisal success and were differentially related to neurotransmitter binding maps, implicating cannabinoid and serotonin systems in reappraisal. These findings challenge limbic-centric models of reappraisal and provide new systems-level targets for assessing and enhancing emotion regulation.

neuroscience↗