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Published in final edited form as: Curr Top Behav Neurosci. 2025;70:127–142. doi: 10.1007/7854_2025_588

The intersection of interoception and anticipation related to pain

Irina A Strigo 1, Alan N Simmons 2
PMCID: PMC13470628  NIHMSID: NIHMS2148271  PMID: 40360927

Abstract

This chapter focuses on the interconnectedness of bodily awareness, emotion, and time perception, focusing on the roles of interoception and anticipation, pioneered by A.D. (Bud) Craig and advanced by contemporary research. Pain, a pivotal aspect of human experience, serves as a conduit for understanding our relationship with the world. Anticipation of pain, vital for survival, influences subjective pain experiences and is modulated by factors such as physiological reactivity and contextual cues. Emotional states significantly shape pain perception, with chronic pain conditions and affective disorders characterized by dysregulated pain modulation mechanisms. We discuss a state space model for pain, wherein pain functions as a latent construct shaped by both anticipatory and contemporaneous factors. Understanding these mechanisms is critical for informing clinical interventions aimed at pain management and highlights the intersection of interoception, emotion, and pain.

Keywords: Interoception, Anticipation, Pain, Emotions, Insula, Emotional Allodynia, State-Space Model, Predictive Coding, Chronic Pain

1. Introduction

The bodily self, emotion, and subjective time are fundamentally linked through the processes of interoception and anticipation. Appreciation of this linkage was pioneered by Bud Craig (Craig, 2002), and has been forwarded by countless other researchers over the last few decades. It was no coincidence that much of the original mapping of these pathways was from the field of pain research, as pain is fundamental to the way that we understand and behave in relationship to the world around us (de C Williams, 2023). To best understand, treat, and predict pain, the brain formulates a predictive model. The premise of most pain as predictive signal model is based on continuously updating pertinent information (Friston, 2003). When sensory evidence fails to confirm the prediction, either the sensory evidence is ignored and, in turn, biases perception, or the brain learns from the error and updates subsequent predictions and evaluations to keep bias in check (Feldman and Friston, 2010; Rigoli et al., 2016). In this chapter, we will review the current work in understanding the role of anticipation in pain through an interoceptive lens.

2. Pain as a modifiable construct

The continual formulation of predictions about future pain is implicit to survival and influences the pain we experience (Fields, 2018; Keltner et al., 2006; Koyama et al., 2005), particularly when the experienced pain in difficult to quantify (Strigo et al., 2024c). Modification of expectation can lead to significant reduction (Tracey, 2010) or amplification (Bingel et al., 2011; Schmid et al., 2015; Schmid et al., 2013) of subjective pain. Thus anticipation of pain is vital in understanding, and clinically addressing, subjective pain (Fields, 2018). One of the key aspects that can strongly influence pain is our emotional state, or psychiatric status, when experiencing pain (Aupperle et al., 2012; Gorka et al., 2017; Grillon et al., 2009; Simmons et al., 2013; Strigo et al., 2008a).

Pain is not solely a physical sensation. According to the International Association for Study of Pain, pain is “an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage” (Raja et al., 2020), (i.e., warning that damage has or could happen or a warning signal of estimated damage). The goal of the pain signal produced in the brain is to motivate action (Craig, 2003b). The physical signal is insufficient to properly determine the correct amount of pain to motivate the correct response as the needed compendium of information may be delayed by seconds, minutes, days, or more. Thus we produce a predictive model (Friston, 2003), not dissimilar from the “interoceptive moment” model by Bud Craig (Craig, 2015). This predictive model depends on: 1) nerve signals, such as from Aδ and C fibers (Craig, 2003c), 2) physiological reactivity (Cowen et al., 2015; Koenig et al., 2014), and context from the 3) anticipated pain onset, 4) contemporaneous pain contextual cues, and 5) expectations of pain offset (Fields, 2018). In this way chronic pain can be seen as an interaction between predicted and contemporaneous information. Related concept is that of “prediction error”, i.e. the mismatch between prediction and afferent information, triggering the behavioral component of pain, the drive/motivation to do something about it (Hoskin and Talmi, 2023). This echoes the theory that chronic pain experience may not be directly linked solely to nociceptive pain (Fields, 2018), rather, it is a state that is influenced by the brain mechanisms of anticipation and expectation, both the anticipation of what pain will be like (onset anticipation) and the expectation that pain will end (offset anticipation).

2.1. The role of anticipation in pain

The construct of anticipation can be categorized into two main types: 1) Acute or imminent threat - where pain occurs immediately following a cue; and 2) prolonged impending threat - where the likelihood of experiencing pain increases over an extended period, often with unpredictable timing. These categories exist along a continuum of the perceived imminence and as expressions of phases of dealing with the perceived threat (Abend, 2023; Fanselow, 2022). There is strong evidence of increased brain activation during anticipation of heat pain versus warm stimuli (Atlas et al., 2010; Ploghaus et al., 1999; Strigo et al., 2010a; Strigo et al., 2008a). Similar networks have been shown when the prolonged, instead of acute, threat of pain is experienced (Abend et al., 2022). In a recent review, Pavy and colleagues suggest that the predictability of pain does not significantly alter pain perception (Pavy et al., 2024), however expectations of pain intensity and basal affective state can moderate these effects. In a sample of 147 chronic pain-free subjects, we saw that large individual differences in the brain of positive and negative pain predictors during unpredictable cues exist even when pain ratings remained similar between subgroups (Strigo et al., 2024c). A key modulator of the pain experience and the experienced anticipation can be contemporaneous information that can lead to biasing (Atlas and Wager, 2012; Geuter et al., 2013).

2.2. The role of emotion in pain

One critical aspect of the pain experience is the interaction with affective state (Lumley et al., 2011). Clinically, mental and physical health are closely linked, and mental health problems and physical health conditions often occur together (Bondesson et al., 2018). Experimentally, this relationship is evidenced by noted differences in pain and pain anticipation across a variety of disorders including depression (Bar et al., 2007; Strigo et al., 2013c; Strigo et al., 2008a), posttraumatic stress (Geuze et al., 2007; Moeller-Bertram et al., 2012; Moeller-Bertram et al., 2014; Strigo et al., 2010b), eating disorders (Strigo et al., 2013b), and traumatic brain injury (Strigo et al., 2018; Strigo et al., 2014). The pain experience itself represents a sophisticated integration of sensory-discriminative components (intensity and location) and affective components (unpleasantness and suffering), deeply rooted in interoceptive processing (Khera and Rangasamy, 2021). While experimental pain stimuli typically create balanced responses between these dimensions in healthy subjects, certain types of sensations like visceral or ischemic stimuli tend to weigh more heavily on the emotional dimension, causing greater suffering even at lower, non-painful intensity levels (Rainville et al., 1992; Strigo et al., 2002). The affective component of sensory processing can be experimentally modulated – changing one’s emotional state affects pain ratings to experimental stimuli, particularly in their affective dimension (Lehoux and Abbott, 2011; Loggia et al., 2008; Villemure and Bushnell, 2002; Zelman et al., 1991). Specifically, negative emotional states like sadness increase the distress associated with the same level of sensory input, an effect that was initially overlooked as most studies only assessed unpleasantness when stimuli were reported as painful. This heightened affective response to sensory stimulation is particularly pronounced in affective disorders, a phenomenon we have termed emotional allodynia (Strigo et al., 2008b) (see below).

This emotional-interoceptive relationship is processed through an interconnected network of brain regions including the insula and anterior cingulate cortex – areas crucial for integrating bodily signals with emotional states (Craig, 2002; Craig, 2015; Critchley and Patchitt, 2024), (see chapter 3&4 in this volume). When individuals experience negative emotions, these same neural circuits show heightened activation, which can prime the brain for enhanced pain perception through altered interoceptive sensitivity. This creates a complex feedback loop where negative emotions can amplify pain perception through enhanced body awareness, and pain can further intensify negative emotions, ultimately affecting how internal bodily signals are processed and interpreted. The role of interoception in this process is particularly evident in how anticipation and emotional context can significantly modify the pain experience even before a stimulus is applied, highlighting how our brain’s anticipation of bodily signals is heavily influenced by emotional state.

2.3. Emotional Allodynia

Emotional allodynia, first described by Strigo et al. (2008) in depression, refers to a phenomenon where individuals experience non-painful stimuli as unpleasant. In this research, depressed individuals rated warm, non-painful temperature stimuli as highly unpleasant, with their unpleasantness ratings matching those that healthy individuals gave to suprathreshold and clearly painful stimuli (Strigo et al., 2008b). The heightened sensitivity to unpleasantness was profound –depressed participants began reporting unpleasantness at temperatures well below both healthy controls’ thresholds and their own pain thresholds. These findings are in direct agreement with literature showing that sensory pain is rated as more distressing by depressed participants (Bar et al., 2010). Importantly, this altered pain perception proved to be a stable characteristic of depression, persisting regardless of attentional states or acute mood changes (Strigo et al., 2008a; Ushinsky et al., 2013), suggesting that emotional allodynia is not simply a reflection of lower baseline affect or increased self-focus found in depression.

A comprehensive meta-analysis by (Thompson et al., 2016) examined pain thresholds across various experimental methods in depression. While results were inconsistent across different types of sensory testing (including electrical, heat, cold, pressure, ischemic), there was one notable exception: all five studies using ischemic stimulation showed consistent findings – individuals with depression demonstrated increased pain sensitivity, reporting pain at significantly lower levels of ischemic stimulation compared to healthy controls (g = −.81; 95% CI, −1.39 to −.24; p = .006). This is particularly noteworthy as ischemic sensations are often experienced as highly unpleasant even if they are not painful (Rainville et al., 1992). Using linear mixed effects modeling of BOLD responses to non-painful warm stimuli applied to the left forearm, our neuroimaging studies revealed a distinct hemispheric lateralization in the insula (see Figure 1). Depression severity showed a strong positive association with increased right insula activation, while emotional allodynia was negatively associated with decreased left insula activation. (total of ~16 ratings)(ICC3, k=0.865, 95%CI: 0.736–0.931, 36 subjects, and 2 raters/measurements; ICC type as referenced by (Shrout and Fleiss, 1979).

Figure 1: Dissociable Anterior Insula Responses to Emotional Allodynia and Depression in Non-Painful Warmth Processing.

Figure 1:

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Linear mixed effects model – non-painful warmth-related BOLD response (anterior insula mask) was regressed against warmth affective bias ratings (emotional allodynia) and depression symptoms severity, as measured by Beck Depression Inventory-2. Activation within the anterior insula showed that emotional allodynia when controlling for depression severity showed association predominantly with the left anterior insula (blue, inverse relationship), while depression severity, when controlling for emotional allodynia showed association predominantly with the right anterior insula (red, positive correlation).

This lateralization aligns with (Craig, 2005) model and is in line with neuroimaging evidence (Strigo and Craig, 2016) showing that the left anterior insula is associated predominantly with parasympathetic activity and positive emotions, whereas the right insula is associated with sympathetic activity and negative emotions. The neural findings within the insula were further supported by heart rate variability (HRV) data, which revealed a significant negative correlation between emotional allodynia and RMSSD (Root Mean Square of the Successive Differences; r=−0.4, p<0.05), which reflects vagally mediated changes in autonomic tone. This sympathovagal imbalance, characterized by low parasympathetic and increased sympathetic tone, has been previously associated with decreased pain tolerance in individuals with somatoform disorder and co-morbid major depression (Pollatos et al., 2011). These findings align with prior research showing lower HRV association with somatic depressive symptoms (Bosch et al., 2009; de Jonge et al., 2007).

The relationship between emotional allodynia and insula function is further supported by (Mutschler et al., 2012), who found evidence of functional reorganization in the insula, with emotion-related responses shifting to areas normally involved in pain processing in healthy individuals. Similarly, (DeVille et al., 2018) linked depression to altered interoceptive processing and insula pathology, showing how disrupted body signal processing may contribute to emotional allodynia. These findings have influenced both theoretical models of interoception, pain and emotion, and practical approaches to treatment. (Garland et al., 2013) integrated this into understanding of chronic pain, showing how negative emotions prime threat processing in affective brain circuits, increasing the likelihood of interpreting bodily sensations as painful. This helps explain the strong epidemiological association between depression and painful conditions (Patten et al., 2015), how depression can increase pain sensitivity following sad mood induction (Lehoux and Abbott, 2011), and poor outcomes in chronic pain conditions (Carroll et al., 2016; Giesecke et al., 2005).

Recent research has expanded our understanding of emotional allodynia’s broader implications. (Raison et al., 2014) connected it to thermoregulatory dysfunction in depression, suggesting altered temperature processing may play a role. Newer treatment approaches have incorporated these insights with developing mindfulness-based pain treatments for chronic pain management (Garland et al., 2023) that also include the “savoring” of positive emotions and positive physical sensations thereby potentially disrupting altered pain appraisals characteristics of emotional allodynia. (Tyler et al., 2024) found that emotional allodynia may influence how depressed individuals respond to thermal interventions, though noting some complexity in the relationship.

3. A neural model of pain

The neural model of pain (Figure 2A, see Chapter 2–4 in this volume for further details) operates through a sophisticated network of interconnected pathways. The primary interoceptive pathway begins with small-diameter (A-delta and C) sensory fibers, which detect thermal, mechanical, and chemical conditions throughout body tissues. These signals are initially processed in lamina I of the spinal cord, then conveyed through a specific thalamic relay to reach the posterior insula, which functions as the primary interoceptive cortex (Craig, 2002, 2003a, c; Craig and Blomqvist, 2002). From here, information is progressively processed along a posterior-to-anterior gradient within the insula. The middle insula serves as an integration hub, combining interoceptive information with hedonic, exteroceptive, and homeostatic motor signals. The anterior insula then incorporates top-down appraisal from the frontal cortex, functioning as the center for subjective awareness. (Craig, 2009b; Craig, 2015; Craig et al., 2000). Running parallel to this main pathway, a secondary projection from lamina I reaches the cingulate cortex, which operates as the limbic motor cortex and is particularly crucial for generating motivational responses and maintaining homeostatic control (Strigo and Craig, 2016). This integrated system becomes further refined through the reward/motivational mesolimbic and interoceptive circuits, where positive or negative attributions of pain are coded (Navratilova and Porreca, 2014; Strigo et al., 2024c). The anterior insula plays a key role in aversive expectation of impending pain (Atlas et al., 2010; Craig, 2009b; Kong et al., 2008; Strigo et al., 2024c), with notable asymmetry – the right anterior insula specifically mediating negative valence emotions (Brooks et al., 2005; Craig, 2005, 2009b; Duerden et al., 2013; Strigo et al., 2013a). In chronic pain conditions, such as back pain, this system can become dysregulated: the reward/motivation circuit shows diminished response (Baliki et al., 2010), potentially impairing pain-escape motivation pain (Goedhoop et al., 2022; Xie et al., 2014), while the interoceptive pathway becomes sensitized, particularly when painful stimuli occur at the site of endogenous pain (Strigo et al., 2021). This comprehensive network forms the neurobiological basis for how we experience, interpret, and respond to pain signals.

Figure 2: Neural Models of Interoception and Pain.

Figure 2:

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A. Schematic of the Neural Circuitry Underlying Interoception and Pain. Based on A.D. (Bud) Craig’s neuroanatomical work. Spinal Lamina I projections (orange) relay through thalamus to cortical targets: interoceptive sensory (posterior insula) and interoceptive motor (anterior cingulate) regions. Interoceptive information flows from posterior insula to middle insula (where it integrates with subcortical inputs), and then to anterior insula (where it integrates with higher-order cortical regions). Known projections are shown with solid arrows. Note: While parabrachial (PB) projections to thalamus (VMb) do not directly project to posterior insula, they likely contribute to anterior insula activity via pathways not yet fully characterized (see Chapter 3). Recent work also reveals feedback loops from anterior insula to brainstem nuclei. B. State-Space Model of Interoception and Pain. This dynamic model illustrates the contemporaneous mechanisms of pain and interoception, color-coded to correspond with neural systems in panel A. Feed-forward effects to predicted states occur within and across layers (dashed arrows). For example, persistent pain perpetuates affective distress. Additionally, avoidance behaviors prevent learning opportunities, reducing modulation of anxiety and helplessness, thus maintaining symptoms. These processes unfold in the context of ongoing physical sensations. Abbreviations: PAG – periaqueductal gray, NTS – nucleus of solitary tract, PB – parabrachial nucleus, VMb – basal ventromedial thalamus, VMpo – posterior ventromedial thalamus, MDvc – mediodorsal thalamus, OFC – orbitofrontal cortex, S1/S2 – primary/secondary somatosensory cortices, vl/dl PFC – ventrolateral/dorsolateral prefrontal cortex, ACC – anterior cingulate cortex

4. A state space model of pain

We have proposed a state space model (Figure 2B) for pain and posttraumatic stress (Strigo et al., 2024a). Similar computational models for pain (Chen and Wang, 2023; Poublan-Couzardot and Talmi, 2024) have been suggested that propose that pain functions as a latent construct in a continuously updating and adjusting dynamic model. Thus, in this way pain is a latent variable constructed by lagged and contemporaneous features, such as information from the nervous system and the contextual situation (Craig, 2015; Pace-Schott et al., 2019). This latent variable is modeled based on the available training data and is dependent on the inputs to this model continuing to operate within the expected range. The latent construct of subjective pain is dependent on expected onset/offset and contemporaneous signals continuing to operate within expected ranges. Thus, emotional trauma or damage to a part of the body can cause signals to operate outside this range causing failure of the model. If re-calibration of the pain model is not possible, due to continued avoidance of pain and/or escape from pain, new training and re-calibration does not occur and the failed model of pain continues in a chronic state. In the case of chronic lower back pain or peripheral neuropathy, the context of pain is specific to the learned prediction that the sensation in the affected body part (e.g., back) or limb (e.g., feet) is indicative of damage or suffering (Baliki et al., 2010; Strigo et al., 2021). Misconceptions on the contemporaneous pain can be substantially modified by anticipation of context and expectations of offset but, unlike these features, we proposed that the contemporaneous assessment is less directly linked to an affective condition than that of predictive evaluations (Strigo et al., 2008a, b). Thus, these components of the pain model (i.e., onset and offset anticipation) line up explicitly with different neuroanatomical substrates outlined above (section 3), such that the “salient self” experienced in the anterior insula functions as the projected future self that is based on the integration of the prior moment, expectations and contemporaneous inputs that update this model. When body signals operate outside our prior experience, the model’s predictions become unreliable, leading to prediction errors that manifest in the context of tissue damage and/or emotional trauma. These prediction errors are then incorporated into the state-space model, affecting how future pain is processed. Emotional allodynia described above (section 2.3) elegantly fits into the state space model of pain by modulation of the processes supporting the anticipation of onset (Strigo et al., 2008a) and offset (Thones and Oberfeld, 2015). While emotional state directly affects regulatory pathways of pain (Fields, 2018), the separation of contemporaneous and affective components does provide leverage into addressing the additive effect of emotional allodynia in pain management.

5. Further considerations

5.1. Interoception and additive models

The model of pain and anticipation presented in this chapter is primarily an interoceptive model (Craig, 2002, 2009b; Craig, 2015). There are other models for the perception of pain that are complimentary to this model. Those include models that are based on animal literature that are more amygdala centric (Thompson and Neugebauer, 2017), models that focus more of the contributions to the perception of pain that come through the sensory motor cortex (Gombaut and Holmes, 2022), models that focus on the modulatory effects of the nucleus accumbens (Altier and Stewart, 1999), and the default mode network, respectively. The advantage of viewing pain through an interoceptive perspective is that, by understanding the integrative function of the insula (particularly its mid and anterior regions) (Barrett and Simmons, 2015), we can conceptualize pain and its anticipation. This approach allows us to consider the complex experience of pain as a hidden variable within a state space model, which can then be used to make clinically relevant predictions.

5.2. Time

Our understanding of when pain will occur shapes how we prepare for and cope with it, showing the fundamental connection between time perception and pain (Fanselow, 2022). This interaction of pain anticipation and time is most likely founded on the use of interoception as the underlying construct that supports both processes. Several chapters in this book elegantly present how time and interoception (Wittmann and Droit-Volet, 2024) and pain and interoception (Mehling, 2024) have key commonalities. Bud Craig’s seminal work (Craig, 2009a) on this matter was key to better understanding how the insula plays a critical role in the intersection of these functions. As described above, the biological goal of pain as a predictive latent variable make the substrates that support this function well tuned for utilization of available internal body signals for mapping specific phases of experience (Wittmann et al., 2010).

5.3. Clinical implications

Understanding pain anticipation has important implications for how we treat people with pain disorders, especially considering mental comorbidities. The latent construct of pain is influenced by anticipation of onset of pain and the expectation of the offset of pain, or pain relief. These factors can be influenced by affective and contemporaneous factors that can help modify the pain experience. An important aspect of keeping the predicted current pain state within normal bounds is to maintain recursive feedback to the model. Thus, approaches that: 1) minimize avoidance, distraction and/or misinterpretations of potential pain signals, such as interoceptive attention training (Mehling et al., 2024; Strigo et al., 2024b), 2) minimize overinterpretation of contemporaneous information, such as mindfulness (Mehling et al., 2025), or 3) minimize escape behavior or exaggeration of the duration of pain, such as exposure therapy (Cayoun et al., 2020), can be important parts of the clinical approaches. Similarly, neurostimulation or pharmacological interventions that help disrupt existent predictive weighting and allow for the formation of predictive pain states that can delay or postpone chronification.

6. Conclusion

A complete interoceptive model of pain anticipation requires appreciation of a multitude of internal and external signals, utilizing prior experience and future predictions (Strigo et al., 2024a). Much of this understanding can be extended to a broad domain of experience beyond pain. Experiences of emotional states and emotional pain may also be viewed within a state space model. However, as pain is critical to survival it may be the core pathway that other systems have coopted to deal with the complexities of being human in our ever more abstracted and complicated experience. The model of interoception forwarded by Bud Craig’s work provides the brain architecture that would logically manifest as a substratum that elegantly combines the complexities of prediction of the homeostatic state, and the interoceptive self in the interoceptive moment.

Funding

This work was supported by in part by the United States Department of Veterans Affairs I01-CX-000816(IAS), I01-CX- 001652(IAS), I01-BX-005918 (ANS), and Painless Research Foundation. Dr. Strigo is a recipient of a Research Career Scientist Award (IK6CX002926) from the Department of Veterans Affairs.

Footnotes

Competing Interests

The authors report no competing interests

Contributor Information

Irina A. Strigo, Veterans Affairs & University of California, San Francisco, San Francisco, CA, USA

Alan N. Simmons, Veterans Affairs & University of California, San Diego, San Diego, CA, USA

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