Acute to Chronic Pain

Mechanisms and Therapeutic Opportunities

May 11-18, 2024

Director: A. Vania Apkarian

Northwestern University, Chicago, USA

Faculty:

Gregory Sherrer, University of North Carolina, Chapel Hill, USA

Johan Vlaeyen, KU Leuven, Belgium & Maastricht University, The Netherlands

Andrea Hohmann, Indiana University, Bloomington, USA

Giandomenico Iannetti, IIT, Rome, Italy & University College, London, UK

Jelena Radulovic, Albert Einstein College of Medicine, New York, USA & Aarhus University, Denmark

A. Vania Apkarian, Northwestern University, Chicago, USA

Guest Lecturer:
Andrew Vigotsky, Northwestern University, Chicago, USA
Andrew Ortony, Northwestern University, Chicago, USA

During this Advanced Course, the neural substrates of pain, from nociception to limbic and cortical circuits, will be thoroughly covered, including the latest ideas pitting localizationist models of perception to perception, engaging the whole nervous system all the time. The discussion will incorporate evidence that can be derived regarding the understanding of pain with fMRI and physiology across species. The latest evidence regarding the mechanisms of the transition from acute to chronic pain will be a major topic, which will be critically analyzed.

Focus will also be placed on the fundamental statistical methods applied to studying pain, including the latest machine learning approaches and multivariable techniques and the extent of their validity and interpretability.

The interplay between fundamental research and its clinical exploitation is a particularly important aspect of pain research. For this reason, dedicated sessions will delve into the latest approaches for drug development, especially for chronic pain, non-pharmaceutical approaches for managing pain, and clinical trial designs.

Pain as a subjective perceived or experienced state continues to influence ideas of what consciousness is and, in turn, defines our social discourse of who we are and how we treat each other and other organisms. The ongoing debate regarding several issues, including whether species like the octopus or the bee are conscious, is intimately linked to the science of pain. This will also be an important component of the Advanced Course.

Greg Scherrer

Pain multidimensionality: neural circuit basis for the sensory-discriminative, affective-motivational, and cognitive-evaluative dimensions of pain experience.

Pain, as an alarm and teaching system, induces adaptive physiological and behavioural responses. The effectiveness of these responses to limit and prevent injuries requires that noxious events are: 1) localized on our body and discriminated from other events, 2) unpleasant and motivated avoidance, and 3) evaluated and that their origin is understood.

In these lectures, we will discuss the spinal and brain ascending circuits by which our nervous system produces each distinct facet of pain experience. We will review crucial findings from studies in humans and animal models that led to the identification of these circuits, from the general anatomical characterization of the regions involved to the discoveries at the molecularly defined neuron-type level. Finally, we will debate the extent to which these advances may facilitate the successful development of more effective and safe therapeutics for a variety of painful conditions.

Jelena Radulovic

Pain and Memory: Processing pain-related stimuli at the circuit and single neuron level

This series of lectures will discuss how brief episodes of painful experiences that do not transition to chronic pain can have long-lasting adverse consequences. Specifically, we will debate the role of memory circuits in the persistent representation of brief, painful experiences. The similarities and differences between persistent emotional distress and chronic pain will be emphasized with respect to the cognitive aspects of negative value processing contributing to both. Most of the research that will be discussed is based on data from rodent models and has a strong neurobiological component focusing on hippocampal circuit and single-cell mechanisms.

 Johan W.S. Vlaeyen

Pain and motivation:  a learning account

Pain is a biologically relevant and vital signal of a bodily threat, urging the individual to protect him/herself. Beyond being a sensory experience, chronic pain is part of a motivational system that alarms, directs, and energizes behavioural actions to minimize impending bodily harm.  This flexible system enables one to learn to predict, prevent and control harmful events in a continuously changing environment. Pain learning reflects a form of plasticity of the nervous system, enabling the organism to respond more adaptively to stimuli due to the continuous stream of changes in the environment. One of the most frequent pain actions is preventing harm by avoiding stimuli associated with pain by direct experience, observation or verbal instruction. These avoidance behaviours can potentially interfere with daily life. Sometimes, it is difficult for individuals to discriminate cues that predict harmful events from those that predict safety. A “better safe than sorry” strategy is then used. Avoiding the cues that potentially predict harm is usually adaptive in the presence of actual harm.

However, avoidance becomes dysfunctional in the absence of such harm and when the costs of avoiding harm cues are higher than their benefits.  Once installed, the extinction of these actions is a difficult and fragile process that occurs after repeated prediction errors. The fragility of extinction is also evidenced by renewal (return of avoidance behaviour in new contexts) and reinstatement (return of avoidance behaviour after an unexpected pain episode). Recent data showing how pain learning terms of predicting and preventing harmful events will be discussed, and how prediction errors can lead to behavioural changes that help the individual reach his valued life goals will also be analysed.

Single-case experimentation

Most of our current knowledge in pain science is derived from research using group-based research designs, sometimes leading to treatment guidelines. Although this methodology has been the gold standard for many decades, the question remains whether the mean effect also represents the effects of the individuals who participated in the trial, let alone any other individual. Using between persons statistical associations to draw conclusions about those associations within one individual is a methodological fallacy. Single-case experimental designs are research designs including repeated measurements over time within a single person under different manipulations of at least one independent variable (e.g., a novel medication or curriculum).

Vania Apkarian

Systems level mechanisms of chronic pain

These lectures will cover systems level current state of understanding of mechanisms of chronic pain. Mechanistic concepts derived from human brain imaging studies as well as complimentary rodent model studies will be discussed. The translational utility of the approach will be presented. Multiple molecules that we are pursuing regarding their potential utility in controlling chronic pain will be presented. In a separate lecture, I will cover the role of placebo and its mechanisms regarding management of chronic pain. Our most recent studies include experiments in rodents vaping fentanyl and chronic pain patients managing their pain with opioids. 

Guest Lecturers:

Andrew Vigotsky  Statistical Modeling and “Machine Learning” in Pain Research and Neuroimaging

Statistical modeling underpins quantitative scientific inferences by providing a framework to interpret data and quantify uncertainty. More recently, investigators—especially in pain neuroimaging—have extended their modeling toolbox to include so-called “machine learning” methods. Unfortunately, many of these methods are applied algorithmically. Is there a better way to think about modeling data to facilitate stronger inferences? In this lecture, we will delve into the theory and (mis)applications of statistical and machine learning methods in pain research. This will include an overview of statistical and modeling principles, concrete examples of model applications and misapplications in pain research, and a tutorial on how to use modeling principles to model your own data. Importantly, this lecture will strongly emphasize modeling concepts rather than algorithmic “rules” that are commonly taught in undergraduate and graduate courses (e.g., when to “use” a t-test vs. ANOVA).

Andrew Ortony  A Cognitive Science Perspective on the Pain-Emotion Connection

In a recent Neuron paper, Gilam at al. (2020) urge a closer interaction between the research fields of pain and emotion, suggesting that pain cannot be fully understood without an answer to the question ‘‘what is an emotion?’’ In this talk I shall propose a defensible conception of emotion and suggest that given the ordinary (and IASP, 1994) understanding of (physical) pain there really is no special connection between pain and emotion. I shall suggest that a close connection between the two is implied by the widespread but technically incorrect claim that pain has an emotional component, and by the misleading juxtaposition of the pleasure and pain in Freud’s famous “Pleasure Principle. It is, of course, true that pain is a major cause of emotion which means that some of their concomitants may cooccur in space and time, a fact that might account for fMRI evidence of shared neural coding.