The frustrating family of pain
What is pain? At first glance this question seems straightforward — almost everyone knows what it feels like to be in pain. We have all felt that shooting sensation when hitting the funny bone, or the dull throb of a headache after a stressful day. There is also much common ground within the scientific community with respect to this question.
Typically, pain is taken to be best defined as a certain kind of mental phenomenon experienced by subjects as pain. For instance, this corresponds to the (still widely accepted) definition of pain given by the International Association for the Study of Pain (1986).
Most cognitive scientists are not merely interested in knowing that various phenomenal experiences qualify as pain from a first-person perspective, however. Instead, pain researchers primarily focus on searching for necessary and sufficient conditions for pain, such that a theory can be developed which allows for informative discriminations and ideally far-reaching generalisations. Pain has proven to be a surprisingly frustrating object of research in this regard.
In the following, I will outline one of the main reasons for this frustration, namely the lack of a sufficient and necessary neural correlate for pain. Subsequently, I will briefly review three solutions to this challenge, arguing that the third is the most promising option.
Neuroscientifically speaking, pain is typically understood as an integrated phenomenon which emerges with the interaction of simultaneously active neural structures that are widely distributed across cortical and subcortical areas (eg Apkarian et al., 2005; Peyron et al., 1999). Interestingly, and perhaps surprisingly, the activation of these neural structures is neither sufficient nor necessary for the experience of pain (Wartolowska, 2011).
Those neural structures that are highly correlated with the experience of pain are not pain-specific (eg Apkarian, Bushnell, & Schweinhardt, 2013), and even the activation of the entire neural network is not sufficient for pain. For instance, itch and pain are processed in the same anatomically defined network (Mochizuki & Kakigi, 2015).
There also does not seem to be any neural structure whose activation is necessary for pain (Tracey, 2011). Even patients with substantial lesions in those neural structures that are often regarded as most central for pain processing are still able to experience pain (e.g. Starr et al., 2009).
Figure 1 Human brain processing pain, retrieved from Apkarian et al. (2005). Original picture caption: Cortical and subcortical regions involved in pain perception, their inter-connectivity and ascending pathways. Location of brain regions involved in pain perception are color-coded in a schematic drawing and in an example MRI.
(a) Schematic shows the regions, their inter-connectivity and afferent pathways. The schematic is modified from Price (2000) to include additional brain areas and connections.
(b) The areas corresponding to those shown in the schematic are shown in an anatomical MRI, on a coronal slice and three sagittal slices as indicated at the coronal slice.
The six areas used in meta-analysis are primary and secondary somatosensory cortices (SI, SII, red and orange), anterior cingulate (ACC, green), insula (blue), thalamus (yellow), and prefrontal cortex (PC, purple). Other regions indicated include: primary and supplementary motor cortices (M1 and SMA), posterior parietal cortex (PPC), posterior cingulate (PCC), basal ganglia (BG, pink), hypothalamus (HT), amygdala (AMYG), parabrachial nuclei (PB), and periaqueductal grey (PAG).
Given the difficulties of characterizing pain by appeal to unique neural structures or a specialized network, some researchers have attempted to characterise pain by appeal to neurosignatures. ‘Neurosignature’ refers to the spatio-temporal activity pattern generated by a network of interacting neural structures (Melzack, 2001).
Thus, neurosignatures are less about the mere involvement of an anatomically defined neural network, but rather about how involved structures are activated and how their activity is coordinated (Reddan & Wager, 2017). Most interestingly, it has been shown that the neurosignature of pain differs from the neurosignature of other somatosensory stimulations, such as itch and warmth (Forster & Handwerker, 2014; Wager et al., 2013).
Unfortunately, different kinds of pain substantially differ with respect to their underlying neurosignatures. For instance, neurosignatures found in patients with chronic pain substantially differ from those of healthy subjects experiencing acute pain (Apkarian, Baliki, & Geha, 2009), because the central nervous system of subjects who live in persisting pain is continuously reorganized as the brain’s morphology, plasticity and chemistry change over time (Kuner & Flor, 2016; Schmidt-Wilcke, 2015).
At most, therefore, we can state that a particular coordination of neural activity is sufficient to distinguish a particular kind of pain from certain non-pain phenomena. However, there seems to be no single neurosignature that is necessary for pain to emerge.
We have arrived at the dilemma that makes pain such a frustrating object of research. On one hand, researchers mostly agree that all and only pains are best defined by means of them being subjectively experienced as pains.
On the other hand, cognitive scientists are unable to identify a single set of neural processes that capture the circumstances under which all and only pains are experienced as such. Thus, the scientific community has been unable to provide an informative and generalizable account of pain.
Two solutions to this dilemma have been offered in the literature.
The first solution involves relinquishing the notion of pain as a certain kind of phenomenal experience, which is an antecedence for most cognitive scientists. Instead, neuroscientific data alone are supposed to be the primary criterion for the identification of pain (eg Hardcastle, 2015).
This solution therefore eliminates the first part of the dilemma. There are two main problems faced by this solution.
Firstly, neural data do not reveal the function of neural structures, networks or signatures by themselves. The function of these neural characteristics are only revealed by their being correlated with some sort of additional data (which, in the case of pain, is typically the subject’s qualification of their own experience as pain). Thus, removing the subjective aspect from pain is analogous to biting the hand that feeds you.
Secondly, serious ethical problems arise when subjective experience is no longer treated as the decisive criterion for the identification of pain. Because neural data may differ from the subjective qualification, this approach may lead to a rejection of medical support for patients that undergo a phenomenal experience of pain. This is a consequence that the majority of contemporary researchers are — for good reasons — unwilling to take (Davis et al., 2018).
As a second solution, one might relinquish the idea that it is possible to develop a single theory of pain. Instead, researchers should focus on the development of separate theories for separate kinds of pain (see, for instance, Jennifer Corns, 2016, 2017). An analogy might illustrate this approach.
The gem class ‘jade’ is unified due to the apparent properties of the respective stones, such as colour and texture. However, in scientific terms the class of jade is composed of jadeite and nephrite, which are of different chemical compositions. Thus, it is possible to develop a theory that enables a distinct characterisation with far-reaching generalisations for either jadeite or nephrite, but not for jade itself (which lacks a sufficient and necessary chemical composition).
Similarly, this solution to the pain dilemma holds that all and only pains are unified due to their phenomenal experience as pain, but they cannot be captured in terms of a single scientific theory. Instead, we need a multiplicity of theories for pain which refer to those subclasses that reveal a necessary and sufficient neural profile.
This solution avoids the methodological and ethical problems faced by the first solution because it is compatible with pains being defined as a certain subjective mental phenomenon. However, because this solution denies that it is possible to develop a single theory of pain, the phenomenon that the scientific community is interested in studying could not thereby be completely accounted for.
If we did develop multiple theories of pain (one for acute pain and one for chronic pain, say), it is far from clear that these theories could explain why all and only pains are subjectively experienced as pain. At best, this might explain why certain cases are acute or chronic pains, but not why they are both pains.
What is missing is a theoretical link that connects the different kinds of pain that, according to this solution, emerge only as independent neural phenomena in separated theories. In terms of the previous analogy, we need something which plays the role of the resemblances in chemical composition between jadeite and nephrite that explains why both of them appear as ‘jade’.
I would like to offer a third solution to the dilemma which avoids the concerns faced by the first solution, and which provides the missing theoretical link required by the more promising second solution. This is to hold a family resemblance theory of pain.
The idea of family resemblance comes from Ludwig Wittgenstein (1953) (although he develops this idea with respect to the meaning of concepts rather than the properties of natural phenomena). A family resemblance theory of pain takes the phenomenal character of pain to unify all and only pains; one’s own subjective experience of pain as such is the criterion of identification that picks out members of the ‘family’ of pain. Moreover, the family resemblance theory of pain denies the presence of an underlying sufficient and necessary neural condition for pain; there is no neural process that distinctively and essentially characterises pain.
Thus, the subjective qualification identifies all and only cases of pain, although they do not share any further necessary or sufficient neural feature. Nonetheless, a family resemblance theory further claims that it is still possible to develop a scientifically useful neurally-based theory of pain that accounts for the phenomenon that the scientific community is interested in.
For this third solution, all and only those phenomena that are experienced as pain are connected through a structure of systematic resemblances that hold between their divergent neural profiles. For instance, consider, again, acute and chronic pain. Both are experienced as pain, and they are substantially different from each other from a neural perspective when directly compared.
However, the transformation from acute to chronic pain is a gradual process, whereby the respective duration of pain correlates with the extent of differences in their neural profile (Apkarian, Baliki, & Geha, 2009). Thus, the neural process of a pain’s first occurrence is relatively similar to its second occurrence, which itself only slightly differs from its third occurrence, and so forth, until it has transformed into some completely different neural phenomenon.
This connection of resemblances over time enables us, however, to explain why subjects experience all of these kinds of pain as pain: acute and chronic pain are bound together under the family resemblance theory through the resemblance relations that hold between the variety of pains that connect them.
Moreover, the family resemblance theory motivates the investigation of pain’s resemblance relations which might prove theoretically as well as practically useful. In further developing research projects of this kind, it appears plausible that, for instance, pains that are more similar to each other are more responsive to the same kind of treatment, even though they do not share a necessary and sufficient neural core property.
Understanding the gradual transition within the resemblance relations that lead from acute to chronic pain might also offer new possibilities of intervention. Thus, instead of developing a separate theory for different kinds of pain, this third approach motivates the investigation of the diversity of neural profiles that occur within the family of pain and of the exact structure of their resemblance relations, and indeed first steps in this direction are already being taken (eg Roy & Wager, 2017).
In sum, when it comes to mental phenomena, such as pain, the underlying neural substrate reaches a complexity and diversity which prevents the identification of necessary and sufficient neural conditions. The family of pain therefore constitutes a frustrating research object.
However, we do not need to throw out the baby with the bathwater and relinquish the definition of pain as a certain kind of mental phenomenon, or the idea of a scientifically useful theory of pain. Of course, a family resemblance theory will be limited with respect to its discriminative and predictive value, since it acknowledges that there is no necessary or sufficient neural substrate for pain.
However, it is the most reductive theory of pain that can be developed in accordance with recent empirical data, and which can account for the fact that all and only pains are experienced as pain.
Apkarian, A. V, Bushnell, M. C., Treede, R.-D., & Zubieta, J.-K. (2005). Human brain mechanisms of pain perception and regulation in health and disease. European Journal of Pain, 9(4), 463–484.
Apkarian, A. V., Baliki, M. N., & Geha, P. Y. (2009). Towards a theory of chronic pain. Progress in Neurobiology, 87(2), 81–97.
Apkarian, A. V., Bushnell, M. C., & Schweinhardt, P. (2013). Representation of pain in the brain. In S. B. McMahon, M. Koltzenburg, I. Tracey, & D. C. Turk (Eds.), Wall and Melzack’s Textbook of Pain (6th ed., pp. 111–128). Philadelphia: Elsevier Ltd.
Corns, J. (2016). Pain eliminativism: scientific and traditional. Synthese, 193(9), 2949–2971.
Corns, J. (2017). Introduction: pain research: where we are and why it matters. In J. Corns (Ed.), The Routledge Handbook of Philosophy of Pain (pp. 1–13). London; New York: Routledge.
Davis, K. D., Flor, H., Greely, H. T., Iannetti, G. D., Mackey, S., Ploner, M., Pustilnik, A., Tracey, I., Treede, R.-F., & Wager, T. D. (2018). Brain imaging tests for chronic pain: medical, legal and ethical issues and recommendations. Nature Reviews Neurology, in press.
Forster, C., & Handwerker, H. O. (2014). Central nervous processing of itch and pain. In E. E. Carstens & T. Akiyama (Eds.), Itch: Mechanisms and Treatment (pp. 409–420). Boca Raton (FL): CRC Press/Taylor & Francis.
Hardcastle, V. G. (2015). Perception of pain. In M. Matthen (Ed.), The Oxford Handbook of Philosophy of Perception (pp. 530–542). Oxford: Oxford University Press.
IASP Subcommitte on Classification. (1986). Pain terms: a current list with definitions and notes on usage. Pain, 24(suppl. 1), 215–221.
Kuner, R., & Flor, H. (2016). Structural plasticity and reorganization in chronic pain. Nature Reviews Neuroscience, 18(1), 20–30.
Melzack, R. (2001). Pain and the neuromatrix in the brain. Journal of Dental Education, 65(12), 1378–1382.
Mochizuki, H., & Kakigi, R. (2015). Central mechanisms of itch. Clinical Neurophysiology, 126(9), 1650–1660.
Peyron, R., García-Larrea, L., Grégoire, M. C., Costes, N., Convers, P., Lavenne, F., Maugière, F., Michel, D., & Laurent, B. (1999). Haemodynamic brain responses to acute pain in humans. Sensory and attentional networks. Brain, 122(9), 1765–1779.
Reddan, M. C., & Wager, T. D. (2017). Modeling pain using fMRI: from regions to biomarkers. Neuroscience Bulletin, 34(1), 208–215.
Roy, M., & Wager, T. D. (2017). Neuromatrix theory of pain. In J. Corns (Ed.), Routledge Handbook of Philosophy of Pain (pp. 87–97). London; New York: Routledge.
Schmidt-Wilcke, T. (2015). Neuroimaging of chronic pain. Best Practice and Research: Clinical Rheumatology, 29(1), 29–41.
Starr, C. J., Sawaki, L., Wittenberg, G. F., Burdette, J. H., Oshiro, Y., Quevedo, A. S., & Coghill, R. C. (2009). Roles of the insular cortex in the modulation of pain: insights from brain lesions. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 29(9), 2684–2694.
Tracey, I. (2011). Can neuroimaging studies identify pain endophenotypes in humans? Nature Reviews. Neurology, 7(3), 173–181.
Wager, T. D., Atlas, L. Y., Lindquist, M. A., Roy, M., Woo, C.-W., & Kross, E. (2013). An fMRI-based neurologic signature of physical pain. The New England Journal of Medicine, 368(15), 1388–1397.
Wartolowska, K. (2011). How neuroimaging can help us to visualize and quantify pain? European Journal of Pain Supplements, 5(2), 323–327.
Wittgenstein, L. (1953). Philosophical investigations. G. E. M. Anscombe & R. Rhees (Eds.). Oxford: Blackwell Publishing.