Human Pain Seminar Series
This series was borne out of the COVID-19 Global Pandemic, which posed significant challenges to the pain community. Its purpose was to reinforce the message that the we—those who do human pain research—are part of a community.
I put together the #WeAreAllInThisTogether COVID-19 Journal Club. It's an opportunity to connect, to remain intellectually stimulated, to learn, and to keep up with the literature.
It has evolved into a Seminar Series that highlights the work of our community, and allows members of the community at any stage of their career engage with the speakers.
We are supported by the University of Toronto Centre for the Study of Pain.
We meet over Zoom every so often - about every 3 weeks. The specifics, papers, and link to the Zoom will be posted here.
We look forward to seeing you all.
Thursday, October 6, 10:00 am EST
Title: A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems
Presented by: Bogdan Petre, PhD student, Wager Lab, Dartmouth College, Hanover, New Hampshire, United States of America
Abstract: Information is coded in the brain at multiple anatomical scales: locally, distributed across regions and networks, and globally. For pain, the scale of representation has not been formally tested, and quantitative comparisons of pain representations across regions and networks are lacking. In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. We compared models based on (a) a single most pain-predictive region or resting-state network; (b) pain-associated cortical–subcortical systems developed from prior literature (“multisystem models”); and (c) a model spanning the full brain. We estimated model accuracy using leave-one-study-out cross-validation (CV; 7 studies) and subsequently validated in 4 independent holdout studies. All spatial scales conveyed information about pain intensity, but distributed, multisystem models predicted pain 20% more accurately than any individual region or network and were more generalizable to multimodal pain (thermal, visceral, and mechanical) and specific to pain. Full brain models showed no predictive advantage over multisystem models. These findings show that multiple cortical and subcortical systems are needed to decode pain intensity, especially heat pain, and that representation of pain experience may not be circumscribed by any elementary region or canonical network. Finally, the learner generalization methods we employ provide a blueprint for evaluating the spatial scale of information in other domains.
Title: Common and stimulus-type-specific brain representations of negative affect
Presented by: Dr. Marta Čeko, Assistant Research Professor, Institute of Cognitive Science, University of Colorado, Boulder, CO, USA
Abstract: The brain contains both generalized and stimulus-type-specific representations of aversive events, but models of how these are integrated and related to subjective experience are lacking. We combined functional magnetic resonance imaging with predictive modeling to identify representations of generalized (common) and stimulus-type-specific negative affect across mechanical pain, thermal pain, aversive sounds and aversive images of four intensity levels each. This allowed us to examine how generalized and stimulus-specific representations jointly contribute to aversive experience. Stimulus-type-specific negative affect was largely encoded in early sensory pathways, whereas generalized negative affect was encoded in a distributed set of midline, forebrain, insular and somatosensory regions. All models specifically predicted negative affect rather than general salience or arousal and accurately predicted negative affect in independent samples, demonstrating robustness and generalizability. Common and stimulus-type-specific models were jointly important for predicting subjective experience. Together, these findings offer an integrated account of how negative affect is constructed in the brain and provide predictive neuromarkers for future studies.
Title: Precise and stable edge orientation signaling by human first-order tactile neurons
Presented by: Dr. Andrew Pruszynski, Canada Research Chair in Sensorimotor Neuroscience Associate Professor, Physiology and Pharmacology, Psychology Principal Investigator, Western Institute of Neuroscience Scientist, Robarts Research Institute Co-director, Sensorimotor Superlab Western University in London, Ontario, Canada
Abstract: Fast-adapting type 1 (FA-1) and slow-adapting type 1 (SA-1) first-order neurons in the human tactile system have distal axons that branch in the skin and form many transduction sites, yielding receptive fields with many highly sensitive zones or 'subfields'. We previously demonstrated that this arrangement allows FA-1 and SA-1 neurons to signal the geometric features of touched objects, specifically the orientation of raised edges scanned with the fingertips. Here we show that such signaling operates for fine edge orientation differences (5-20°) and is stable across a broad range of scanning speeds (15-180 mm/s); that is, under conditions relevant for real-world hand use. We found that both FA-1 and SA-1 neurons weakly signal fine edge orientation differences via the intensity of their spiking responses and only when considering a single scanning speed. Both neuron types showed much stronger edge orientation signaling in the sequential structure of the evoked spike trains and FA-1 neurons performed better than SA-1 neurons. Represented in the spatial domain, the sequential structure was strikingly invariant across scanning speeds, especially those naturally used in tactile spatial discrimination tasks. This speed invariance suggests that neurons' responses are structured via sequential stimulation of their subfields. Indeed, the spatial precision of elicited action potentials rationally matched spatial acuity of subfield arrangements, which typically corresponds to the dimension of individual fingertip ridges. The present results further the idea that the terminal branching of first-order tactile neurons constitutes a peripheral neural mechanism supporting the identification of tactile geometric features.
Title: The neural signature of the decision value of future pain
Dr. Mathieu Roy, Assistant Professor, Research Chair (Tier 2) on brain imaging of pain, Department of Psychology, McGill University, Canada
Dr. Michel-Pierre Coll, Adjunct Professor, School of Psychology, Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS), Université Laval, Québec, Canada
Abstract: Pain is a primary driver of action. We often must voluntarily accept pain to gain rewards. Conversely, we may sometimes forego potential rewards to avoid associated pain. In this study, we investigated how the brain represents the decision value of future pain. Participants (n = 57) performed an economic decision task, choosing to accept or reject offers combining various amounts of pain and money presented visually. Functional MRI (fMRI) was used to measure brain activity throughout the decision-making process. Using multivariate pattern analyses, we identified a distributed neural representation predicting the intensity of the potential future pain in each decision and participants’ decisions to accept or avoid pain. This neural representation of the decision value of future pain included negative weights located in areas related to the valuation of rewards and positive weights in regions associated with saliency, negative affect, executive control, and goal-directed action. We further compared this representation to future monetary rewards, physical pain, and aversive pictures and found that the representation of future pain overlaps with that of aversive pictures but is distinct from experienced pain. Altogether, the findings of this study provide insights on the valuation processes of future pain and have broad potential implications for our understanding of disorders characterized by difficulties in balancing potential threats and rewards.