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, N¼137). 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, N¼46), 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

Somatic and Vicarious Pain are Represented by Dissociable Multivariate Brain Patterns

Understanding how humans represent others’ pain is critical for understanding pro-social behavior. ‘Shared experience’ theories propose common brain representations for somatic and vicarious pain, but other evidence suggests that specialized circuits are required to experience others’ suffering. Combining functional neuroimaging with multivariate pattern analyses, we identified dissociable patterns that predicted somatic (high versus low: 100%) and vicarious (high versus low: 100%) pain intensity in out-of-sample individuals. Critically, each pattern was at chance in predicting the other experience, demonstrating separate modifiability of both patterns. Somatotopy (upper versus lower limb: 93% accuracy for both conditions) was also distinct, located in somatosensory versus mentalizing-related circuits for somatic and vicarious pain, respectively. Two additional studies demonstrated the generalizability of the somatic pain pattern (which was originally developed on thermal pain) to mechanical and electrical pain, and also demonstrated the replicability of the somatic/vicarious dissociation. These findings suggest possible mechanisms underlying limitations in feeling others’ pain, and present new, more specific, brain targets for studying pain empathy

Brain Representations and Mechanisms of Pain Experience and Regulation: a Multivariate Pattern Approach

For the last two decades, functional Magnetic Resonance Imaging (fMRI) revolutionized how we study human cognition and emotion. However, as evidence accumulates, many of the human brain-function mappings that fMRI studies have produced appear to be flawed due to their poor sensitivity, specificity, and reproducibility. A new emerging paradigm, which we termed predictive modeling, has a potential to resolve these issues. This new approach is based on specific uses of machine learning techniques combined with experimental designs optimized for prediction, yielding well-defined neuroimaging signatures of brain-outcome relationships that can be prospectively tested in new individuals, studies, and translational applications. In this dissertation, I first reviewed the state of translational neuroimaging and discussed how we can move the field forward using the predictive modeling approach (Chapter I). Then, I examined neural representations of pain and related emotions using pattern recognition techniques. More specifically, in Chapter II, I identified fMRI multivariate patterns that are sensitive and specific to physical pain and social rejection and assessed the relationship between two patterns. 60 participants who recently experienced an unwanted romantic break-up were scanned with fMRI while they experienced physical pain and social rejection stimuli on separate trials. I found that the multivariate patterns for pain and rejection are uncorrelated and separately modifiable at the whole-brain level and within many brain regions, such as the dorsal anterior cingulate, anterior and dorsal posterior insular, and secondary somatosensory cortices that have shown overlapping fMRI activity with univariate methods. In Chapter III, I developed an fMRI multivariate pattern signature that characterizes the cerebral processes that contribute to pain beyond the level of nociceptive input and mediate psychological and behavioral influences. The new signature was developed based on data from 4 independent studies that involved thermal pain stimulation (N = 137) and included patterns of fMRI activity in nucleus accumbens, lateral prefrontal, parahippocampal, and other regions. We then prospectively tested the new signature on 2 independent test datasets (Studies 5-6, N = 46), and showed that the signature responses explained variation in trial-by-trial pain ratings not reflected in a previous fMRI-based marker for nociceptive pain. In addition, the signature responses mediated the pain-modulating effects of three psychological manipulations of expectation and perceived control. In Chapter IV and V, I further examined whether different psychological pain modulation methods influence primary nociceptive system or other cognitive and affective ones. In Chapter IV, 33 participants engaged in cognitive self-regulation to increase or decrease pain while experiencing multiple levels of painful heat. I found that both heat intensity and self-regulation strongly influenced reported pain, but they did so via two distinct brain pathways. The effects of stimulus intensity were mediated by the neurologic pain signature (NPS), an a priori distributed brain network shown to predict physical pain with over 90% sensitivity and specificity across four studies. Self-regulation did not influence NPS responses; instead, its effects were mediated through functional connections between the nucleus accumbens and ventromedial prefrontal cortex. This pathway was unresponsive to noxious input, and has been broadly implicated in valuation, emotional appraisal, and functional outcomes in pain and other types of affective processes. In Chapter V, 20 participants experienced painful heat while distracting cognitive tasks were crossed with an expectation-based placebo treatment. I found that distracting tasks reduced pain though increased activity of the fronto-parietal control network (FPN) and decreased activity of the NPS. However, placebo treatment had n

Deconstructing Pain: Sensory and Cognitive Manipulations of Pain are Mediated by Distinct Systems

Cognitive strategies can strongly modulate emotion and pain. However, it is unclear whether cognition primarily influences core affective processes or later decision and valuation processes. We combined fMRI imaging with an experimental pain paradigm, and concurrently manipulated both the intensity of noxious input and a cognitive reappraisal of pain. Both manipulations strongly influenced reported pain, but they did so via two distinct brain pathways. The effects of stimulus intensity were mediated by a distributed brain network recently shown to predict physical pain with over 90% sensitivity and specificity across four studies. Cognitive reappraisal had no effect on activity in this network. Instead, cognitive effects on pain were mediated through a pathway connecting the nucleus accumbens and ventromedial prefrontal cortex. This pathway was unresponsive to noxious input, and has been broadly implicated in valuation and emotional appraisal. These findings suggest that sensory and cognitive manipulations influence pain through distinct brain pathways

Neural mechanisms of pain relief through paying attention to painful stimuli

Copyright © 2021 International Association for the Study of Pain.ABSTRACT: A commonly held belief suggests that turning one's attention away from pain reduces it, whereas paying attention to pain increases it. However, some attention-based therapeutic strategies for pain, such as mindfulness-based interventions, suggest that paying attention to painful stimuli can reduce pain, resulting in seemingly contradictory conclusions regarding attention and pain. Here, we investigated the analgesic effects of attention modulation and provide behavioral and neural evidence that paying attention to pain can reduce pain when attention is directed toward the specific features of painful stimuli. The analgesic effects of paying attention to painful stimuli were mediated by the primary somatosensory cortex and goal-directed attention regions in the prefrontal and parietal cortex. These findings suggest that suppressing early somatosensory processing through top-down modulation is the key mechanism of the analgesic effects of paying attention to painful stimuli, providing evidence that pain itself can be used as a component of pain management.11Nsciescopu

Post-Stroke Cognitive Impairment: Pathophysiological Insights into Brain Disconnectome from Advanced

The neurological symptoms of stroke have traditionally provided the foundation for functional mapping of the brain. However, there are many unresolved aspects in our understanding of cerebral activity, especially regarding high-level cognitive functions. This review provides a comprehensive look at the pathophysiology of post-stroke cognitive impairment in light of recent findings from advanced imaging techniques. Combining network neuroscience and clinical neurology, our research focuses on how changes in brain networks correlate with post-stroke cognitive prognosis. More specifically, we first discuss the general consequences of stroke lesions due to damage of canonical resting-state large-scale networks or changes in the composition of the entire brain. We also review emerging methods, such as lesion-network mapping and gradient analysis, used to study the aforementioned events caused by stroke lesions. Lastly, we examine other patient vulnerabilities, such as superimposed amyloid pathology and blood-brain barrier leakage, which potentially lead to different outcomes for the brain network compositions even in the presence of similar stroke lesions. This knowledge will allow a better understanding of the pathophysiology of post-stroke cognitive impairment and provide a theoretical basis for the development of new treatments, such as neuromodulation.11Nsciescopuskc

False-positive neuroimaging: Undisclosed flexibility in testing spatial hypotheses allows presenting anything as a replicated finding

© 2019 Elsevier Inc. Hypothesis testing in neuroimaging studies relies heavily on treating named anatomical regions (e.g., “the amygdala”) as unitary entities. Though data collection and analyses are conducted at the voxel level, inferences are often based on anatomical regions. The discrepancy between the unit of analysis and the unit of inference leads to ambiguity and flexibility in analyses that can create a false sense of reproducibility. For example, hypothesizing effects on “amygdala activity” does not provide a falsifiable and reproducible definition of precisely which voxels or which patterns of activation should be observed. Rather, it comprises a large number of unspecified sub-hypotheses, leaving room for flexible interpretation of findings, which we refer to as “model degrees of freedom.” From a survey of 135 functional Magnetic Resonance Imaging studies in which researchers claimed replications of previous findings, we found that 42.2% of the studies did not report any quantitative evidence for replication such as activation peaks. Only 14.1% of the papers used exact coordinate-based or a priori pattern-based models. Of the studies that reported peak information, 42.9% of the ‘replicated’ findings had peak coordinates more than 15 mm away from the ‘original’ findings, suggesting that different brain locations were activated, even when studies claimed to replicate prior results. To reduce the flexible and qualitative region-level tests in neuroimaging studies, we recommend adopting quantitative spatial models and tests to assess the spatial reproducibility of findings. Techniques reviewed here include permutation tests on peak distance, Bayesian MANOVA, and a priori multivariate pattern-based models. These practices will help researchers to establish precise and falsifiable spatial hypotheses, promoting a cumulative science of neuroimagin

Neural signatures of individual variability in context-dependent perception of ambiguous facial expression

© 2022 The Author(s)How do we incorporate contextual information to infer others’ emotional state? Here we employed a naturalistic context-dependent facial expression estimation task where participants estimated pleasantness levels of others’ ambiguous expression faces when sniffing different contextual cues (e.g., urine, fish, water, and rose). Based on their pleasantness rating data, we placed participants on a context-dependency continuum and mapped the individual variability in the context-dependency onto the neural representation using a representational similarity analysis. We found that the individual variability in the context-dependency of facial expression estimation correlated with the activity level of the pregenual anterior cingulate cortex (pgACC) and the amygdala and was also decoded by the neural representation of the ventral anterior insula (vAI). A dynamic causal modeling revealed that those with higher context-dependency exhibited a greater degree of the modulation from vAI to the pgACC. These findings provide novel insights into the neural circuitry associated with the individual variability in context-dependent facial expression estimation and the first empirical evidence for individual variability in the predictive accounts of affective states.11Nsciescopu

Functional brain reconfiguration during sustained pain

Pain is constructed through complex interactions among multiple brain systems, but it remains unclear how functional brain networks are reconfigured over time while experiencing pain. Here, we investigated the time-varying changes in the functional brain networks during 20 min capsaicin-induced sustained orofacial pain. In the early stage, the orofacial areas of the primary somatomotor cortex were separated from other areas of the somatosensory cortex and integrated with subcortical and frontoparietal regions, constituting an extended brain network of sustained pain. As pain decreased over time, the subcortical and frontoparietal regions were separated from this brain network and connected to multiple cerebellar regions. Machine-learning models based on these network features showed significant predictions of changes in pain experience across two independent datasets (n = 48 and 74). This study provides new insights into how multiple brain systems dynamically interact to construct and modulate pain experience, advancing our mechanistic understanding of sustained pain.11Nsciescopu