Lauren Y. Atlas

A Meta-analysis of Brain Mechanisms of Placebo Analgesia: Consistent Findings and Unanswered Questions

Placebo treatments reliably reduce pain in the clinic and in the lab. Because pain is a subjective experience, it has been difficult to determine whether placebo analgesia is clinically relevant. Neuroimaging studies of placebo analgesia provide objective evidence of placebo-induced changes in brain processing and allow researchers to isolate the mechanisms underlying placebo-based pain reduction. We conducted formal meta-analyses of 25 neuroimaging studies of placebo analgesia and expectancy-based pain modulation. Results revealed that placebo effects and expectations for reduced pain elicit reliable reductions in activation during noxious stimulation in regions often associated with pain processing, including the dorsal anterior cingulate, thalamus, and insula. In addition, we observed consistent reductions during painful stimulation in the amygdala and striatum, regions implicated widely in studies of affect and valuation. This suggests that placebo effects are strongest on brain regions traditionally associated with not only pain, but also emotion and value more generally. Other brain regions showed reliable increases in activation with expectations for reduced pain. These included the prefrontal cortex (including dorsolateral, ventromedial, and orbitofrontal cortices), the midbrain surrounding the periaqueductal gray, and the rostral anterior cingulate. We discuss implications of these findings as well as how future studies can expand our understanding of the precise functional contributions of the brain systems identified here.

Brain mediators of the effects of noxious heat on pain

Summary We used multi‐level mediation analysis to identify regions in which trial‐by‐trial responses to heat explained variability in the relationship between noxious stimulus intensity and perceived pain. ABSTRACT Recent human neuroimaging studies have investigated the neural correlates of either noxious stimulus intensity or reported pain. Although useful, analyzing brain relationships with stimulus intensity and behavior separately does not address how sensation and pain are linked in the central nervous system. In this study, we used multi‐level mediation analysis to identify brain mediators of pain—regions in which trial‐by‐trial responses to heat explained variability in the relationship between noxious stimulus intensity (across 4 levels) and pain. This approach has the potential to identify multiple circuits with complementary roles in pain genesis. Brain mediators of noxious heat effects on pain included targets of ascending nociceptive pathways (anterior cingulate, insula, SII, and medial thalamus) and also prefrontal and subcortical regions not associated with nociceptive pathways per se. Cluster analysis revealed that mediators were grouped into several distinct functional networks, including the following: somatosensory, paralimbic, and striatal‐cerebellar networks that increased with stimulus intensity; and 2 networks co‐localized with “default mode” regions in which stimulus intensity‐related decreases mediated increased pain. We also identified “thermosensory” regions that responded to increasing noxious heat but did not predict pain reports. Finally, several regions did not respond to noxious input, but their activity predicted pain; these included ventromedial prefrontal cortex, dorsolateral prefrontal cortex, cerebellar regions, and supplementary motor cortices. These regions likely underlie both nociceptive and non‐nociceptive processes that contribute to pain, such as attention and decision‐making processes. Overall, these results elucidate how multiple distinct brain systems jointly contribute to the central generation of pain.

Pain in the ACC

Lieberman and Eisenberger (1) claim that the “dorsal anterior cingulate cortex (dACC) is selective for pain.” This surprising conclusion contradicts a large body of evidence showing robust dACC responses to nonpainful conditions. Electrophysiological and optogenetic studies have identified neuronal populations activated during foraging behavior, attention, emotion, reward expectancy, skeletomotor and visceromotor activity, and other functions (e.g., refs. 2⇓⇓–5). Only a small minority of dACC neurons are pain-related.

Instructed knowledge shapes feedback-driven aversive learning in striatum and orbitofrontal cortex, but not the amygdala

Socially-conveyed rules and instructions strongly shape expectations and emotions. Yet most neuroscientific studies of learning consider reinforcement history alone, irrespective of knowledge acquired through other means. We examined fear conditioning and reversal in humans to test whether instructed knowledge modulates the neural mechanisms of feedback-driven learning. One group was informed about contingencies and reversals. A second group learned only from reinforcement. We combined quantitative models with functional magnetic resonance imaging and found that instructions induced dissociations in the neural systems of aversive learning. Responses in striatum and orbitofrontal cortex updated with instructions and correlated with prefrontal responses to instructions. Amygdala responses were influenced by reinforcement similarly in both groups and did not update with instructions. Results extend work on instructed reward learning and reveal novel dissociations that have not been observed with punishments or rewards. Findings support theories of specialized threat-detection and may have implications for fear maintenance in anxiety. DOI: http://dx.doi.org/10.7554/eLife.15192.001

Quantifying cerebral contributions to pain beyond nociception

Cerebral processes contribute to pain beyond the level of nociceptive input and mediate psychological and behavioural influences. However, cerebral contributions beyond nociception are not yet well characterized, leading to a predominant focus on nociception when studying pain and developing interventions. Here we use functional magnetic resonance imaging combined with machine learning to develop a multivariate pattern signature—termed the stimulus intensity independent pain signature-1 (SIIPS1)—that predicts pain above and beyond nociceptive input in four training data sets (Studies 1–4, N=137). The SIIPS1 includes patterns of activity in nucleus accumbens, lateral prefrontal and parahippocampal cortices, and other regions. In cross-validated analyses of Studies 1–4 and in two independent test data sets (Studies 5–6, N=46), SIIPS1 responses explain variation in trial-by-trial pain ratings not captured by a previous fMRI-based marker for nociceptive pain. In addition, SIIPS1 responses mediate the pain-modulating effects of three psychological manipulations of expectations and perceived control. The SIIPS1 provides an extensible characterization of cerebral contributions to pain and specific brain targets for interventions.

Prepared stimuli enhance aversive learning without weakening the impact of verbal instructions

Fear-relevant stimuli such as snakes and spiders are thought to capture attention due to evolutionary significance. Classical conditioning experiments indicate that these stimuli accelerate learning, while instructed extinction experiments suggest they may be less responsive to instructions. We manipulated stimulus type during instructed aversive reversal learning and used quantitative modeling to simultaneously test both hypotheses. Skin conductance reversed immediately upon instruction in both groups. However, fear-relevant stimuli enhanced dynamic learning, as measured by higher learning rates in participants conditioned with images of snakes and spiders. Results are consistent with findings that dissociable neural pathways underlie feedback-driven and instructed aversive learning.

Pain neuroimaging in humans: a primer for beginners and non-imagers

Human pain neuroimaging has exploded in the past 2 decades. During this time, the broader neuroimaging community has continued to investigate and refine methods. Another key to progress is exchange with clinicians and pain scientists working with other model systems and approaches. These collaborative efforts require that non-imagers be able to evaluate and assess the evidence provided in these reports. Likewise, new trainees must design rigorous and reliable pain imaging experiments. In this article we provide a guideline for designing, reading, evaluating, analyzing, and reporting results of a pain neuroimaging experiment, with a focus on functional and structural magnetic resonance imaging. We focus in particular on considerations that are unique to neuroimaging studies of pain in humans, including study design and analysis, inferences that can be drawn from these studies, and the strengths and limitations of the approach. Perspective: This article provides an overview of the concepts and considerations of structural and functional magnetic resonance neuroimaging studies. The primer is written for those who are not familiar with brain imaging. We review key concepts related to recruitment and study sample, experimental design, data analysis and data interpretation.

Pain or nociception? Subjective experience mediates the effects of acute noxious heat on autonomic responses

Abstract Nociception reliably elicits an autonomic nervous system (ANS) response. Because pain and ANS circuitry interact on multiple spinal, subcortical, and cortical levels, it remains unclear whether autonomic responses are simply a reflexive product of noxious stimulation regardless of how stimulation is consciously perceived or whether the experience of pain mediates ANS responses to noxious stimulation. To test these alternative predictions, we examined the relative contribution of noxious stimulation and individual pain experience to ANS responses in healthy volunteers who underwent 1 or 2 pain assessment tasks. Participants received 8 seconds of thermal stimulation of varied temperatures and judged pain intensity on every trial. Skin conductance responses and pupil dilation responses to stimulation served as measures of the heat-evoked autonomic response. We used multilevel modelling to examine trial-by-trial relationships between heat, pain, and ANS response. Although both pain and noxious heat stimulation predicted skin conductance response and pupil dilation response in separate analyses, the individual pain experience statistically mediated effects of noxious heat on both outcomes. Furthermore, moderated mediation revealed that evidence for this process was stronger when stimulation was perceived as painful compared with when stimulation was perceived as nonpainful. These findings suggest that pain appraisal regulates the heat-evoked autonomic response to noxious stimulation, documenting the flexibility of the autonomic pain response to adjust to perceived or actual changes in environmental affordances above and beyond nociceptive input.

Multiple Brain Pathways Mediate Expectancy Effects on Pain

•Expectancies modulate both reported pain and responses in some brain regions, yet the key brain circuitry that mediates expectancy effects on pain experience has not been identified. –Placebo expectancy manipulations: decreases in “pain matrix” regions1,2, increases in control regions, particularly rACC2,3,4 –Placebo analgesia brain-behavior correlations = between-subjects only. –Event-related (cue-based) expectancy manipulations: modulation of pain matrix and striatal regions5,6 –Have not examined relationship between brain and pain reports. •For a brain region or pathway to mediate expectancy effects on reported pain, its activity must: a) be influenced by expectancy. b) predict trial-by-trial changes in reported pain, even within a single level of noxious stimulation. c) statistically explain a significant portion of expectancy effects on trial-by-trial reported pain. •We used multi-level mediation (M3) software to test this compound hypothesis, and to locate regions that formally mediate the relationship between experimentally manipulated expectancy and reported pain. Multiple brain pathways mediate expectancy effects on pain Lauren Y. Atlas1, Niall Bolger1, Martin Lindquist2, Tor D. Wager1 1Columbia University Department of Psychology, 2Columbia University Department of Statistics

Modeling Brain Pathways using Functional Mediation Analysis

The unit of analysis is a 3-variable path model (Fig. 1). Mediating variables (M) explain the relationship between two other variables (X and Y), implying a functional path through the mediator. In our implementation, two variables, X and Y, are scalars, while the mediating variable M is functional. In the data we present here, for example, X is a series of temperatures applied to skin, Y is the pain reported after each stimulation, and M is a time series of brain data following each stimulation (that will be treated as samples from a continuous underlying function). The relationship between the variables is expressed using the equations: