Pain and the Perception of Space in Fibromyalgia: Effects of Pain in Estimations of Distance

doi:10.21203/rs.3.rs-4249265/v1

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Pain and the Perception of Space in Fibromyalgia: Effects of Pain in Estimations of Distance

https://doi.org/10.21203/rs.3.rs-4249265/v1

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The Economy of action hypothesis postulates that bodily states rescale the perception of the individual’s environment’s spatial layout. The estimation of distances and slopes in navigation space (i.e. the space reachable by locomotion) is influenced by sensations relating to body condition and the metabolic cost of the actions. The results of the studies investigating the impact of pain on distance estimation remain inconclusive. 28 women suffering from chronic pain and fibromyalgia (FM), and 24 healthy controls (HC) were assessed for musculoskeletal, neuropathic, and visceral pain. In a VR-mediated task, they observed a 3D scenario and estimated the distance of a flag positioned at different distances (1, 2, 3, 4 or 5m) on virtual ramps with either a 4% or 24% inclination. Overestimation of distances in the steeper ramp condition was expected, if participants executed the task by internally simulating the movement.

The results showed a dissociation between the effects of musculo-skeletal and visceral-neuropathic pain on distance estimations. According to the Economy of action hypothesis, the HCs estimated the distances as being farther away when the ramp was more inclined (i.e. at 3m and 5m and with a 24% inclination). Furthermore, visceral and neuropathic pain were found to affect the performance of this group. In contrast, there was no effect related to the different ramp inclinations in the FM group, indicating that in the presence of chronic widespread pain, automatic, bodily-based estimations of the potential cost of actions in space are compromised.

Biological sciences/Psychology

Biological sciences/Psychology/Human behaviour

Biological sciences/Neuroscience

Biological sciences/Neuroscience/Cognitive neuroscience

Biological sciences/Neuroscience/Cognitive neuroscience/Perception

Embodied cognition theories

Fibromyalgia

Space Perception

Visceral pain

Neuropathic pain

Musculoskeletal pain

The role of the body and sensorimotor information in cognitive functions and social interactions represents the conceptual fulcrum of a set of theories gathered under the label of Embodied Cognition Theories (ECT, Barsalou, 2008). This approach suggests that not only action representations but also higher-order processing, such as judgment capacities, the use of abstract concepts in language (e.g. metaphors, Lakoff & Johnson, 1980) or the creation of cultural artefacts, are grounded on the sensory and motor body/brain flow of information (Gallagher, 2005). From this perspective, cognitive symbols are simulations of the bodily states built during previous sensorimotor experiences (the ‘sensorimotor contingencies’, Barsalou, 2008).

Within the ECT, the Embodied Perception Theory (Proffitt, 2006b) focuses on the perception of the external world, and states that the representation of objects and space is not a mere function of perceptual systems but rather involves adaptive processes emerging from the interdependent relationship between the state of the body and the environment (Friston, 2011; Proffitt, 2006b). In this sense, an individual’s navigation space (i.e. the space within which individuals can move around to reach targets or explore the environment by locomotion) is the result of the integration of sensory information (i.e. from visual, auditory or tactile stimuli) and the internal mental simulation of the movement which is potentially to be performed (e.g. moving toward a distant target within the space).

In this process of internal simulation, the current state of the body impacts space perception and distance estimations. For example, actions requiring higher metabolic consumption necessitate rescaling the perception of the space to navigate in, with an overestimation of the distances involved. Similarly, altering the amount of effort required, for example asking someone to wear a heavy backpack, leads to an overestimation of the inclination of a slope (Bhalla & Proffitt, 1999) and the distances involved (Proffitt et al., 2003). The same happens when an individual’s blood glucose levels are low (Cole & Balcetis, 2013). Indeed, according to the Economy of Action hypothesis (Proffitt, 2006b), when individuals are asked to walk to reach a specific target, their perception of the distance is modulated by the effort specifically implied by the act of walking and not by other actions, for example throwing an object (Witt et al., 2004).

Crucially, these effects are present only if individuals represent moving their bodies and not when they base their judgment exclusively on visual information. In effect, the overestimation of greater distances disappears when the possibility of motion is limited. This is the case of people suffering from spinal cord injury and paraplegia (i.e. paralysis in the lower part of the body) who estimate the distances of objects in the space exclusively relying on visual cues when the possibilities of moving in space are perceived as reduced (i.e. when they are not sitting in their own wheelchair). On the contrary, similarly to healthy people, they activate the internal motor simulation when they are on their own wheelchair (Scandola, Togni, et al., 2019).

The aim of the current study is to understand the potential modulatory effects of pain on the perception and estimation of distances. Chronic pain is known to affect body representations in terms of action representations (Coslett et al., 2010; Schwoebel et al., 2001) and motor imagery (Scandola et al., 2022), but its effects on the perception of navigation space are inconclusive (MacIntyre et al., 2022; Tabor et al., 2013; Witt et al., 2009), probably because of the complex and multifactorial nature of pain.

Indeed, pain may represent a temporary or chronic condition (i.e. when symptoms persist past an inciting event or the healing process lasts for more than 3 months, Apkarian et al., 2011) and may manifest in different typologies, such as musculoskeletal pain (affecting osteoarticular and muscular structures, El-Tallawy et al., 2021), neuropathic pain (caused by a damage in the central or peripheral nervous system, IASP, 2023), or visceral pain (caused by inflammation or disease, or damage or injury involving internal organs, Collett, 2013). The chronic presence of one or more of these typologies of pain is usually related to clinical conditions; however, the experience of temporary pain is also widespread in the general, undiagnosed population. Musculoskeletal pain is reported in around half of the general population (47%, El-Tallawy et al., 2021), while neuropathic pain is more specific to pathological conditions (from 7–8% in the undiagnosed population, Bouhassira, 2019). Visceral pain is a common experience and may occur as a result of a variety of conditions, ranging from a feeling of discomfort due to simple indigestion to extreme discomfort in cases of, for example, renal colic (Collett, 2013).

This study aims at investigating the effects of the different types of chronic pain on individual’s perception of the navigation space. For this reason, we chose to interview participants who suffer from Fibromyalgia, and their responses were compared to those of a gender and age-matched control group. Fibromyalgia (FM) is a clinical condition characterised by widespread, chronic primary pain (ICD-11 – code MG30.01; Berwick et al., 2022; Treede et al., 2019). The prevalence of FM reaches 5.8% of the population in industrially developed countries (Ablin et al., 2012; Branco et al., 2010; Wolfe et al., 2013), and it is more frequent in women (8–10:1, female to male ratio). The pain that characterizing FM is typically chronic since they report having experienced pain since childhood or youth, and this has lasted over time with a certain degree of stability. Furthermore, other symptoms that make this syndrome a perfect model for the purposes of investigating the Economy of Action Hypothesis are the sense of chronic fatigue and sleep disorders, including non-restorative sleep. Physical exhaustion and cognitive difficulties, in particular involving memory (Wolfe et al., 2016), anxiety and depression (Häuser et al., 2015; Schweiger et al., 2022) have also been reported.

After the clinical data collection, FM and control participants were asked to perform a task in a virtual reality environment, and to estimate the distance between their body and a flag positioned at various distances on a virtual ramp presented with two different degrees of inclination. According to the Economy of Action Hypothesis, increasing flag distances, in particular when associated with steeper ramp inclination, should lead to an overestimation of distance. However, we postulated that this would also be influenced by the intensity and typology of pain and the sense of fatigue experienced by the participants. If internal simulation of the movement is adopted to estimate objects’ distance, higher pain intensity should result in an overestimation of objects’ distances depicted on a steeper ramp, while, in the case that pain prevents the use of this strategy in favour of a purely visual estimation, the errors in estimation should not change for different slopes. Finally, there is the possibility that different typologies of pain (i.e. temporary and chronic pain, musculoskeletal, visceral and neuropathic pain) could impact in different ways on the performance.

Participants

28 women suffering from fibromyalgia (FM, age = 48.4 ± 10.9, years of education = 12.3 ± 3.6) and 24 healthy control participants (i.e. without diagnoses of neurological illness or other conditions associated with chronic pain, HC, age = 49.9 ± 10.2, education = 14.8 ± 2.6) were recruited at the Analgesic Therapy Unit, Borgo Roma Hospital, Verona (Italy) and at the Rehabilitation Department in the IRCSS Sacro Cuore Hospital (Negrar, Verona, Italy) (Table 1). The diagnosis of fibromyalgia was confirmed in the FM group by means of the combined scores on the Widespread Pain Index (WPI) and the Symptom Severity Scale (SSS) (Wolfe et al., 2018). The WPI is a self-reported pain index resulting from the number of painful regions out of the 19 regions considered in the Regional Pain Scale (Wolfe, 2003) (score range = 0–19). The SSS is the result (range 0–12) of the sum of the severity scores of 3 symptoms (i.e. fatigue, waking unrefreshed, and cognitive symptoms, score range for each item = 0–3), along with the sum of the number of other symptoms that might have co-occurred during the previous 6 months (i.e. headaches, pain or cramps in the lower abdomen, and depression – score 0–3) (Wolfe et al., 2018). A combination of WPI ≥ 7 and SSS ≥ 5 or WPI ≥ 4 and SSS ≥ 9 was considered as the two valid cut-offs for a diagnosis of FM. This means in fact that in the FM group, pain had been present in at least 4 or 5 regions for at least 3 months (with pain in the jaw and chest and abdominal pains not included in the list). It is to be noted that, following these diagnostic criteria (Wolfe et al., 2018), a diagnosis of FM is considered to be valid irrespective of other diagnoses and does not exclude the presence of other serious clinical illnesses (Wolfe et al., 2018). The same scales were administered to the control group.

The sample was consistent with an a-priori sample size that was computed by means of data simulations using a beta = 0.68 (Scandola, Togni and colleagues (2019), for the script see OSF repository at https://osf.io/fmys5/). According to the simulation, a minimum sample size of 24 participants per group was necessary to achieve a 95% credible interval of the posterior distribution completely outside, or completely within the Region of Practical Equivalence (the “range of parameter values that are equivalent to the null value for practical purposes”, Kruschke, 2018, p. 272). The participants read and signed the informed consent form. The study was approved by the Ethics committee of the Province of Verona (Prot. N. 2147cesc) and was conducted in accordance with the Declaration of Helsinki (2013). The same participants had previously participated in another study (Scandola et al., 2022).

Table 1

**Demographic data and clinical assessment of the participants in the two groups**. FM = participants with fibromyalgia; HC = healthy control (details for the diagnosis in the text). WPI = Widespread Pain Index (Wolfe et al., 2016, 2018); SSS = Symptom Severity Scale (Wolfe et al., 2016, 2018); HADS = Hospital Anxiety-Depression Scale (Bjelland et al., 2002); VMIQ = Vividness of Motor Imagery Inventory (Roberts et al., 2008); EVI = Explicit Visual Imagery; K = Kinaesthetic Imagery; Age and Education are reported in years. MAX = Maximum, MIN = minimum and an Index (log[(maximum + 1) * (minimum + 1)]) are reported for each typology of pain assessed by means of the Verona Pain Questionnaire (VPQ). The average between Visceral and Neuropathic pain is reported in the last three columns. See results (section Preliminary analysis of pain self-evaluations) for details.
ID	WPI	SSS	Age	Education	HADS		VMIQ		VPQ Muscolo-Skeletal Pain			VPQ Visceral Pain			VPQ Neuropathic Pain			VPQ Visceral - Neuropathic average
					Anxiety	Depression	EVI	K	MAX	MIN	Index	MAX	MIN	Index	MAX	MIN	Index	MAX	MIN	Index
FM01	12	7	63	5	9	4	40	30	6	0	1.95	6	0	1.95	6	0	1.95	6.00	0.00	1.95
FM02	15	9	52	8	11	0	34	20	8	5	3.99	0	0	0.00	0	0	0.00	0.00	0.00	0.00
FM03	8	6	47	16	16	12	34	38	8	0	2.20	10	0	2.40	0	0	0.00	5.00	0.00	1.20
FM04	14	11	53	13	8	9	47	40	7	1	2.77	7	1	2.77	9	0	2.30	8.00	0.50	2.54
FM05	18	10	54	8	11	9	47	44	8	6	4.14	10	0	2.40	0	0	0.00	5.00	0.00	1.20
FM06	10	7	53	8	10	8	52	50	10	7	4.48	8	0	2.20	6	0	1.95	7.00	0.00	2.07
FM07	19	11	52	13	10	10	48	44	10	7	4.48	10	8	4.60	10	8	4.60	10.00	8.00	4.60
FM08	18	11	57	13	17	15	58	56	10	7	4.48	10	7	4.48	10	7	4.48	10.00	7.00	4.48
FM09	12	8	34	16	7	3	35	46	9	3	3.69	0	0	0.00	6	0	1.95	3.00	0.00	0.97
FM10	11	10	52	16	15	6	46	51	9	4	3.91	8	5	3.99	0	0	0.00	4.00	2.50	1.99
FM11	16	11	54	13	11	3	55	56	8	1	2.89	8	0	2.20	0	0	0.00	4.00	0.00	1.10
FM12	10	11	51	18	6	8	36	41	4	4	3.22	8	4	3.81	7	2	3.18	7.50	3.00	3.49
FM13	12	9	20	13	14	2	25	28	8	2	3.30	9	2	3.40	0	0	0.00	4.50	1.00	1.70
FM14	11	11	23	13	8	4	24	40	10	4	4.01	10	6	4.34	0	0	0.00	5.00	3.00	2.17
FM15	14	10	43	13	6	1	39	41	6	3	3.33	8	6	4.14	10	6	4.34	9.00	6.00	4.24
FM16	7	8	58	13	11	1	26	26	10	0	2.40	5	5	3.58	9	1	3.00	7.00	3.00	3.29
FM17	12	9	53	13	7	3	48	44	10	4	4.01	9	0	2.30	9	0	2.30	9.00	0.00	2.30
FM18	13	10	44	13	7	9	53	53	10	0	2.40	0	0	0.00	10	5	4.19	5.00	2.50	2.09
FM19	10	8	57	13	5	2	35	41	8	3	3.58	10	0	2.40	10	0	2.40	10.00	0.00	2.40
FM20	14	10	48	13	11	1	30	27	10	0	2.40	8	0	2.20	0	0	0.00	4.00	0.00	1.10
FM21	18	9	53	8	6	2	60	60	9	0	2.30	7	0	2.08	8	2	3.30	7.50	1.00	2.69
FM22	8	11	40	16	5	6	60	60	10	5	4.19	8	3	3.58	0	0	0.00	4.00	1.50	1.79
FM23	18	11	54	8	5	11	50	50	10	5	4.19	9	5	4.09	10	8	4.60	9.50	6.50	4.34
FM24	11	9	58	16	9	8	40	41	9	4	3.91	8	2	3.30	10	0	2.40	9.00	1.00	2.85
FM25	6	11	32	13	10	5	38	40	10	2	3.50	6	0	1.95	0	0	0.00	3.00	0.00	0.97
FM26	19	8	51	10	15	8	60	60	10	0	2.40	9	0	2.30	10	0	2.40	9.50	0.00	2.35
FM27	16	9	35	11	5	2	12	12	8	0	2.20	10	0	2.40	10	4	4.01	10.00	2.00	3.20
FM28	19	12	45	20	8	5	31	31	10	0	2.40	10	1	3.09	10	0	2.40	10.00	0.50	2.74
Mean	13.25	9.54	47.71	12.61	9.39	5.61	41.54	41.79	8.75	2.75	3.31	7.54	1.96	2.71	5.71	1.54	1.99	6.63	1.75	2.35
Median	12.50	10.00	52.00	13.00	9.00	5.00	40.00	41.00	9.00	3.00	3.42	8.00	0.00	2.40	7.50	0.00	2.30	7.00	0.75	2.24
Std. Dev.	3.89	1.53	10.55	3.42	3.52	3.89	12.39	12.29	1.55	2.46	0.83	2.99	2.63	1.27	4.51	2.70	1.71	2.77	2.39	1.17
HC01	7	4	52	13	8	3	36	35	8	2	3.30	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC02	3	7	52	13	12	3	31	35	6	0	1.95	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC03	2	6	46	16	10	3	33	28	9	3	3.69	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC04	5	6	19	13	13	3	39	40	6	1	2.64	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC05	6	6	56	8	10	2	18	18	10	0	2.40	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC06	2	5	51	13	11	4	17	19	10	0	2.40	4	0	1.61	0	0	0.00	2.00	0.00	0.80
HC07	6	6	52	16	13	4	19	40	10	3	3.78	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC08	5	4	48	13	13	4	25	13	3	0	1.39	0	0	0.00	6	0	1.95	3.00	0.00	0.97
HC09	1	5	57	16	10	2	18	23	8	0	2.20	9	0	2.30	8	0	2.20	8.50	0.00	2.25
HC10	6	1	57	18	15	3	18	22	8	0	2.20	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC11	3	8	56	18	8	7	42	60	8	0	2.20	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC12	6	5	58	13	10	4	38	44	10	1	3.09	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC13	4	1	44	16	14	4	12	12	8	2	3.30	0	0	0.00	8	0	2.20	4.00	0.00	1.10
HC14	2	7	54	16	11	6	28	32	6	2	3.04	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC15	0	1	57	16	10	4	13	12	0	0	0.00	4	0	1.61	0	0	0.00	2.00	0.00	0.80
HC16	0	1	54	13	10	8	23	18	0	0	0.00	4	0	1.61	0	0	0.00	2.00	0.00	0.80
HC17	4	6	34	16	12	3	37	27	0	0	0.00	0	0	0.00	8	2	3.30	4.00	1.00	1.65
HC18	3	3	37	21	11	3	28	19	7	0	2.08	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC19	4	5	58	13	11	8	41	60	6	2	3.04	0	0	0.00	7	0	2.08	3.50	0.00	1.04
HC20	6	6	51	13	7	11	23	33	7	0	2.08	0	0	0.00	10	0	2.40	5.00	0.00	1.20
HC21	5	7	53	13	11	5	43	44	6	1	2.64	9	0	2.30	0	0	0.00	4.50	0.00	1.15
HC22	1	6	43	18	8	7	35	30	3	0	1.39	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC23	1	6	22	13	10	2	29	22	5	0	1.79	0	0	0.00	0	0	0.00	0.00	0.00	0.00
HC24	1	2	46	16	13	7	29	19	5	0	1.79	6	0	1.95	0	0	0.00	3.00	0.00	0.97
Mean	3.46	4.75	48.21	14.75	10.39	4.62	28.57	29.68	6.21	0.71	2.18	1.50	0.00	0.47	1.96	0.08	0.59	1.73	0.04	0.53
Median	3.50	5.50	52.00	14.50	10.00	4.00	29.00	29.00	6.50	0.00	2.20	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
Std. Dev.	2.17	2.15	10.66	2.66	2.39	2.16	9.91	13.34	3.11	1.04	1.06	2.89	0.00	0.85	3.52	0.41	1.07	2.28	0.20	0.66

Experimental task

Virtual reality scenarios

Two virtual reality (VR) scenarios were designed in 3DS max 2015 (Autodesk, Inc.), implemented in XVR2.0 and displayed through a head mounted display (HMD) Oculus Rift DK1.

The first scenario aimed at verifying the participants’ general ability to estimate distances and controlling for any difference in sensitivities with regard to the perception of depth in a VR environment (baseline task). In this scenario, a flag was depicted in an open space in front of the participant, placed at various distances (from 0.5 to 8m, with graduations of 0.5m). The target distances used in the main task (i.e. 1, 2, 3, 4 and 5m) were shown five times, while the other distances were shown only once with the mere purpose of reducing learning effects and habituation. A total of 36 stimuli were presented. The participants were requested to verbally estimate the distance of each flag from the perceived position of their own body. The data related to the target distances were then used to normalise the individual’s perceptual errors in the main experimental task.

In the main experimental scenario, two features of the stimuli, previously found to impact the estimation of distances (Proffitt, 2006b; Scandola et al., 2019), were manipulated: i) the distance of the target and ii) the inclination of the surface. For this reason, this main scenario was identical to the baseline scenario, with the exception that in this case the flag was placed on a ramp shown in front of the participant. The stimuli thus differed in terms of the inclination of the ramp, that could be mild (4% corresponding to 7°) or steep (24%, i.e. 13.5°, Fig. 1), as well as in terms of the distance of the flags from the participant (i.e. 1, 2, 3, 4 or 5 m). Each distance/inclination combination was presented 5 times in random order, for a total of 50 stimuli in each of the two experimental conditions (i.e. with the participant sitting or standing, see below). In both scenarios, each stimulus was shown for 1s.

Questionnaires

In addition to the measures collected during the experiment, data on the types of pain were recorded by means of a questionnaire (Scandola et al., 2017). Furthermore, due to the nature of the experimental task, the potential impact of the participants’ motor imagery abilities was checked (Roberts et al., 2008). Finally, as mood disorders have been reported in fibromyalgia patients (Häuser et al., 2015), depression and anxiety were controlled (Bjelland et al., 2002).

Assessment of Pain.

In order to have a comprehensive evaluation of the different typologies of pain, the participants filled in the Verona Pain Questionnaire (VPQ, Scandola et al., 2017), which comprises a scale which differentiates between musculoskeletal, visceral and neuropathic pain, the scores for which show a high degree of correlation with both the Brief Pain inventory (Caraceni et al., 1996) and the Douleur Neuropathique 4 scale (Bouhassira et al., 2005).

In particular, the VPQ requires a self-evaluation of the minimum and maximum level of musculoskeletal, neuropathic, and visceral pain in the last two weeks, on a scale ranging from 0 (no pain at all) to 10 (worst imaginable pain) (Scandola et al., 2017).

Assessment of Motor Imagery.

To estimate Motor Imagery abilities, two subscales of the Visual Motor Imagery Questionnaire-2 (VMIQ, Isaac et al., 1986; Roberts et al., 2008) were used. The subscale External Visual Imagery (VMIQ-EVI) asks the participants to imagine themselves performing 12 actions as if they are looking at themselves from a third-person perspective (“as if you were watching yourself from an external position”). The Kinaesthetic Imagery subscale (VMIQ-K) requires participants to imagine the somatosensory feelings associated with the execution of the same actions. In both conditions, the actions are not actually performed but only imagined. Thus, the two subscales involve different cognitive processes, specifically visual imagery in the former and the simulation of bodily sensations in the latter (Ionta et al., 2010; Moro et al., 2021; Scandola et al., 2017). The participants are asked to estimate the vividness of each action imagined, on a 5-point Likert scale (with 1 = perfectly vivid imagined action and 5 = not imagined at all). The sums of the scores are considered as the final scores for each subscale (score range = 12–60, with lower scores indicating better motor imagery).

Assessment of anxiety and depression

To control for the potential effects of mood on the two groups’ performances, the Hospital Anxiety and Depression Scale (HADS, Bjelland et al., 2002) was used. The questionnaire, which provides a scale that gives scores for anxiety and depression, consists in 14 multiple-choice questions investigating the frequency (1 = never, 5 = always) with which a specific mood occurs (e.g. “I feel agitated and tense”; “I feel in a good mood”).

Procedure

Participants sat in a comfortable chair and were interviewed by the examiner in order to fill in the preliminary questionnaires (VPQ, VMIQ, HADS). After this, they wore the HMD and anti-noise headphones to isolate them from the environment. In a preliminary phase, they freely explored the VR environment.

The procedure was the same for both the baseline and the experimental tasks, with the only difference being that the baseline task was executed with the participant sitting in a comfortable chair, while the experimental task consisted of two conditions: a Standing condition (in which the participants had to complete the task while standing) and a Sitting condition (in which the task was executed with the participant sitting in a comfortable chair). These two conditions served to control the effects of any feelings of fatigue associated with the execution of the task and were presented in a counterbalanced order across participants. The stimuli in the baseline and experimental tasks were shown in random order for 1s. For each stimulus, the participants were requested to estimate the distance of the flag from themselves in centimetres and respond verbally. There were no time constraints.

After the baseline task and the main task in each of the two conditions (i.e. sitting and standing), the participants were asked to evaluate their current level of fatigue and pain on a visual analogue scale (10cm long VAS, from “no pain” or “no fatigue” to “maximum pain” or “maximum fatigue”).

Data Handling and Statistical Analyses

Preliminary analyses: Localised v. Widespread Pain and differences between Musculoskeletal, Visceral and Neuropathic Pain

One of the key features of pain in FM (that also represents a diagnostic criterion) is that it is not localised, but spread, involving different body parts (Wolfe et al., 2018). Thus, in order to confirm a difference in the degree of pain spread between the two groups, the WPI scores of FM and HC participants were compared by means of a Bayesian Linear Model with Group as independent variable.

Another preliminary analysis regarding the typologies of pain was carried out. Notwithstanding the fact that the diagnosis of FM is based on musculoskeletal pain, other typologies of pain (i.e. neuropathic and visceral pain) are often reported by FM patients (Costantini et al., 2017; Gauffin et al., 2013; Rehm et al., 2010). For this reason, since the study focuses on the potential effects of pain on distance estimation, a preliminary analysis was performed to check whether differences might arise with respect to the typology of pain in the two groups. An index of pain was calculated for each type of pain, accounting for both the minimum and maximum pain intensity: log[(maximum + 1) * (minimum + 1)], ranging between 0 (no pain) and 4.79 (worse minimum and maximum pain, both scored 10). A Bayesian Linear Model was used, with Group and Type of Pain (musculoskeletal, visceral and neuropathic) as independent variables and slope of Type of Pain grouped by participant as a random effect in order to control for within-subjects variability. The prior distributions were two Gaussian distributions (mean = 0, sd = 1 for the regressors and mean = 0, sd = 5 for the intercept) which were chosen as they have a good sensitivity with regard to the differences between the various types of pain and the groups (the regressors), but a wide overall mean range (the intercept). A series of five models were fitted, starting from a null model (i.e. only intercept, no regressors) to the saturated model (i.e. all regressors and interactions). The model that best represented the data was chosen by means of posterior probabilities based on marginal likelihoods (Gronau et al., 2020). The results of these preliminary statistical analyses suggested an absence of differences between Visceral and Neuropathic pain which were then averaged in the subsequent analyses (see Results section).

The experimental Virtual Reality task: distance estimation

An analysis of the baseline task was carried out to confirm that the distances used in the task were perceived by the participants as being progressively farther away (see Supplementary Materials, SM1). Bayesian analyses with non-informative priors were used to analyse the errors in estimating the distances and the VASs of current fatigue and pain. The inference was based on 89% Highest Posterior Density Intervals (89%HPDI) of posterior distributions (McElreath, 2016) and the Region of Practical Equivalence (ROPE, Kruschke & Liddell, 2018). ROPEs were computed as the range for a negligible effect size (Cohen, 1988), namely the interval within − 0.1 * SD, + 0.1 * SD (note that the intervals of computed ROPEs will be reported at the beginning of each analysis). This means that when the 89% HPDI is completely outside the ROPE, the null hypothesis can be rejected.

In the analysis of the distance estimations, the dependent variable was the Error in estimation, calculated as the difference between the actual and estimated distances of the flag, and converted into a z-score by means of an established procedure (Scandola, Togni, et al., 2019), using as a reference the mean and standard deviations for each distance in the baseline task (see SM1 for the analysis of the raw data of baseline estimations that confirm that participants were able to discriminate different levels of depth; see Eq. 1 for the formula used to compute the z-scores). The use of this index allowed us to limit potential biases within the sample (i.e. heteroskedasticity, extreme values) and to standardize depth perception, that in a virtual reality environment can largely vary (Lampton et al., 1995).

$${z}_{exp,distance={d}_{i,},subj={s}_{j}}=\frac{{err}_{exp,distance={d}_{i,},subj={s}_{j}}-M\left({err}_{baseline,distance={d}_{i,},subj={s}_{j}}\right)}{S\left({err}_{baseline,distance={d}_{i,},subj={s}_{j}}\right)}$$

Eq. 1: Computation of z-scores of the main experiment. The subscript “exp” indicates the “main experiment”, “baseline” the “baseline task”, “distance” refers to a particular distance ${d}_{i}$(the computation was executed for all distances one by one), “subj” represents a specific participant ${s}_{j}$(the computation was executed for all participants one by one), ‘M’ stands for the mean function, and ‘S’ represents the standard deviation function.

The fixed effects of the Bayesian Linear Model were the Condition (Seated, Standing), the inclination of the Ramp (4%, 24%), the Group (FM, HC), and the Distance of the flag (1, 2, 3, 4 or 5m). Since the distance from the flag might impact evaluations linearly or non-linearly, polynomial contrasts were used to capture non-linear relations (linear, quadratic, cubic and fourth order).

Moreover, the index of musculoskeletal pain and the average index of visceral and neuropathic pain were used as covariates in interaction with the other fixed effects. As random effects, we used the intercept of the individual participant and the intercept of the interaction between the participant and all of the within-subject factors (Condition, Ramp and Distance) in order to avoid pseudo-replication biases (Scandola & Tidoni, 2023).

Moreover, to determine whether the hypothetical effects on the estimation of distances were specifically related to pain or influenced by other factors, such as abilities in motor imagery and mood variables (Häuser et al., 2015), two further models were fitted, using as covariates the scores in the VMIQ subscales and the Anxiety and Depression subscales of the HADS, respectively.

To analyse any changes in fatigue and pain (i.e. the VAS estimations) after the Baseline task, and in the Standing and Sitting conditions of the experimental paradigm, a Bayesian Linear Model was used with the Group and the Condition as fixed effects, and the intercept of the participants and the intercept of the interaction between the participants and the within-subjects factor Condition as random effects.

Only the effects that show 89% HPDI (thus making it possible to reject the null hypothesis) are reported. However, the complete list of results is shown in the Supplementary Materials (Tables SM2 – for the analysis with musculoskeletal and visceral-neuropathic pain as covariates, SM3 – for the analysis with motor imagery scores as covariates and SM4 – for the analysis with depression and anxiety scores as covariates), including the Gelman-Rubin convergence diagnostic (Ȓ, Vehtari et al., 2021), the Bulk and Tail Estimated Sample Size (ESS, Vehtari et al., 2021), the Posterior Predictive Checking (Gelman, 2013), (in all cases, Ȓ ≤ 1.01, ESS > 500, and Posterior Predictive Checking show that the fitted models are compatible with the data).

All the Bayesian models were fitted with 4 chains with 1000 warmup iterations and 1000 sampling iterations, for a total of 4000 iterations.

The statistical analyses were conducted on R 4.2.2 (R Core Team, 2022), using brms 2.18.0 (Bürkner, 2018) and emmeans (Lenth, 2022) for post-hoc testing.

Preliminary analyses: Widespread v. Localised Pain and comparisons among Musculoskeletal, Visceral and Neuropathic Pain.

In order to confirm that pain sensations were more spread in the FM group than in the HC group, the WPI scores were analysed. This analysis confirmed that pain was more spread in the FM group than in the HCs as there was a difference in the number of painful body regions between the groups (M = 0.71, 89% HPDI = 0.62, 0.80, ROPE = -0.61, 0.61). The mean number of painful areas in the FM group was 13.47 (SD ± 3.87), while the HCs reported on average 3.23 areas of pain (± 2.34). Full details are in the Supplementary Materials SM5 and SM6.

As far as the typology of pain is concerned, the analyses of the indexes of pain intensity experienced by the participants showed that the model with both main factors (Group and Type of Pain), but not their interaction, was the best model (Table 2A). In particular, the results showed higher pain levels in the FM group (2.66 ± 1.42) than in the HCs (1.08 ± 1.29), without any differences between the types of pain experienced. By analysing the main effect of the typologies of pain (Table 2B), we found that visceral (1.58 ± 1.55) and neuropathic pain (1.28 ± 1.56) could be merged into a unique pain evaluation (see Table 2B), while musculoskeletal pain (2.74 ± 1.16) was more severe (i.e. higher scores) than the former pain sensations. Considering these results, the visceral and neuropathic pain evaluations were then averaged in the subsequent analyses.

Table 2

**Comparisons between Bayesian Linear Models on the index of pain.** The posterior model probability is an index in a 0–1 range that allows Bayesian model comparison. A) comparison among models with different regressors. Comparison between “Type of Pain + Group” and “Type of Pain * Group” models show a Bayes Factor = 12.4 in favour of the former model; B) Comparisons among models where it was tested if specific pain sensations have identical scores. Comparison between the “(Visceral = Neuropathic) ≠ Musculoskeletal” and “Neuropathic ≠ Visceral ≠ Musculoskeletal” models show a Bayes Factor = 3.36 in favour of the “(Visceral = Neuropathic) ≠ Musculoskeletal” model. The mean, median and standard deviation values for the two groups are shown in Table 1.
A)	Model	Posterior probability
	Type of Pain * Group	0.2
	Type of Pain + Group	0.8
	Group	0.0
	Type of Pain	0.0
	Null	0.0
B)	Equality	Posterior probability
	Neuropathic ≠ Visceral ≠ Musculoskeletal	0.23
	(Neuropathic = Musculoskeletal) ≠ Visceral	0.00
	(Visceral = Musculoskeletal) ≠ Neuropathic	0.00
	(Visceral = Neuropathic) ≠ Musculoskeletal	0.77
	Visceral = Neuropathic = Musculoskeletal	0.00

The experimental Virtual Reality task: distance estimation

Distance estimation and pain were analysed for the main task in a single model (see Data Handling and Statistical Analysis). However, to simplify the explanation of the results, the effects will be reported separately.

The ROPE for this analysis was between − 0.10 and 0.10.

The estimation of distances in Healthy Controls and Fibromyalgia patients

The results showed the main effects of Linear Distance (M = 1.83, 89%HPDI = 1.73, 1.92) and the interaction between Group and Quadratic Distance (M = 0.25, 89%HPDI = 0.15, 0.34) indicating different non-linear trends in the two groups. Furthermore, an interaction between Ramp Inclination, Group and Linear Distance (M = -0.25, 89%HPDI = -0.37, -0.11) was found. No conclusive effects were observed for Condition (sitting/standing) and its interactions (see the Supplementary Materials Table SM2).

A post-hoc analysis of the Ramp:Group:Distance interaction only showed a difference in the estimation errors in the HC group when the 4% and the 24% ramp inclinations were compared at 3m (M = -0.42, 89%HPDI = -0.75, -0.102) and 5m (M = -0.84, 89%HPDI = -1.16, -0.51). According to the hypothesis, for this group, steeper ramps were associated with larger errors involving an overestimation of distances, indicating that the flags were estimated as being further away when the inclination was steeper. In contrast, this effect was not present in the FM group. All of the HPDIs overlapped the ROPE, meaning that the results were inconclusive.

Comparing the two groups in trials with the steeper ramp (i.e. 24%), the HC participants made larger overestimation errors at the 3m distance than the FM participants (M = -0.79, 89%HPDI = -1.15, -0.49), as well as at 4m (M = -0.61, 89%HPDI = -0.93, -0.27) and also at 5m (M = -0.42, 89%HPDI = -0.78, -0.12). An inverse pattern emerged in trials with the 4% ramp and the flag at 5m, where the HCs made smaller errors than the FM group (M = 0.49, 89%HPDI = 0.13, 0.82). There was a difference in the distance estimates made by the HC group with respect to the 4% and 24% ramps, while no differences were found for the FM group whose estimates were not influenced by the inclination of the slopes. All the other comparisons between the groups were inconclusive. For a graphical representation, see Fig. 2 and Table 3, and Table SM2 in the Supplementary Materials for the inconclusive effects.

Table 3

**Mean and standard deviations of the z-scores of the Errors in the estimation of distances**, computed using as normative values the scores from the baseline scenario, divided by Group (FM = Fibromyalgia participants, HC = Healthy Controls), Distance (1 m, 2 m, 3 m, 4 m and 5 m) and Ramp (4% and 24%)
	FM		HC
Distance	4%	24%	4%	24%
1 m	-0.531 (0.443)	-0.524 (0.458)	-0.555 (0.546)	-0.557 (0.557)
2 m	-0.215 (0.356)	-0.215 (0.365)	0.061 (0.383)	0.049 (0.38)
3 m	0.508 (0.922)	0.506 (0.86)	0.834 (0.707)	1.189 (0.766)
4 m	0.97 (0.464)	0.948 (0.473)	0.984 (0.394)	1.27 (0.415)
5 m	1.908 (0.579)	1.853 (0.595)	0.885 (1.141)	1.807 (0.673)

The effects of pain on distance estimation

Considering the participants as a whole (both FM and HC), it was found that the intensity of visceral-neuropathic pain (as quantified in the pain index) impacted distance estimations. In particular, this index covaried with Distance (M = 0.21, 89%HPDI = 0.14, 0.28), thus indicating that the more severe the pain reported, the farther away the flags were perceived to be.

A post-hoc analysis showed that only the errors made at the 5m distance covaried with the visceral-neuropathic pain index, with a direct relationship (M = 0.27, 89%HPDI = 0.17, 0.37) (see Fig. 3, Table SM2 for the inconclusive results). However, although this effect was present in the HC group at 5m (M = 0.41, 89%HPDI = 0.23, 0.60), the errors made by the FM group overlapped with the ROPE (M = 0.11, 89%HPDI = 0.05, 0.23). In order to determine whether this effect was related to visceral or neuropathic pain in the HC group, explorative correlations between the distance estimations and the neuropathic and visceral pain indexes were computed. The correlation between visceral pain and erroneous estimations at the 5m distance was rho = 0.32, while the correlation between neuropathic pain and erroneous estimations was rho = 0.19, suggesting that the effect was mainly linked to visceral pain in HC.

The effects of body positions on fatigue and pain

The VAS measuring Pain and Fatigue revealed a difference between the two groups (Pain: M = 21.22, 89% HPDI = 15.78, 27.63, ROPE = -3.42, 3.42; Fatigue: M = 21.59, 89% HPDI = 15.96, 27.77, ROPE = -3.64, 3.64), with the FM group always suffering from fatigue (FM = 63.06 ± 34.48, HC = 19.84 ± 22.36) and from Pain (FM = 53.61 ± 31.55, HC = 11.14 ± 18.48) more than the HC group. Inconclusive effects were observed for Condition (i.e. sitting or standing) and for the Group:Condition interaction in both VAS analyses. No modulation of the feelings of pain or fatigue due to the body position was found.

Effects of motor imagery and mood

Neither the model analysing the erroneous distance estimations using the VMIQ subscales as covariates nor the model using the Anxiety and Depression subscales of the HADS as covariates revealed any effects of motor imagery or mood on the estimations. The complete results are reported in Tables SM3 and SM4.

No differences between the HC and FM groups in their self-evaluations of Anxiety and Depression were observed (Anxiety: M = -0.24, 89% HPDI = -0.96, 0.96, ROPE = -0.35, 0.35; Depression: M = 0.68, 89% HPDI = -0.06, 1.28, ROPE = -0.33, 0.33).

A difference in Motor Imagery was found between the two groups in both the VMIQ-EVI (M = 6.82, 89% HPDI = 4.49, 9.26, ROPE = -1.33, 1.33) and VMIQ-K (M = 6.37, 89% HPDI = 3.80, 9.08, ROPE = -1.39, 1.39) subscales, with the FM group performing worse than the HCs. For the descriptive statistics, see Table 1.

The study tested the hypothesis of the potential role of pain and sense of fatigue in the representation of navigation space (i.e. the space within which individuals move around to reach targets or explore the environment) and compared a clinical sample of women suffering from fibromyalgia to a control group. The participants performed a task requiring them to estimate the distance of a target (a flag) that was positioned on an inclined ramp. The inclination was either mild (4%) or steep (24%). The presence of pain was not excluded in the control group, but while the FM group was characterised by chronic, widespread pain, the control sample reported specific conditions of localised pain (Table SM5 and SM6 for details). We anticipated that the presence of pain would impact the distance estimations, in particular resulting in overestimations of the greater distances and when the ramp was steeper. This hypothesis would be in accordance with the Embodied Perception Theory, according to which greater distances and steeper inclinations are imagined to require greater efforts when individuals mentally travel through space to reach a target (Proffitt, 2006a). In order to induce a sense of fatigue, the experimental task was executed in two conditions, one in which the participants were seated and another in which they were standing. However, these two conditions did not impact the results, although the FM group always reported greater levels of fatigue than the control group.

The results revealed that, although a general effect of overestimation of distances was present in both groups, a dissociation emerged with regard to their responses. Specifically, while in the case of the HC group the steeper inclination (i.e. 24%) was associated with larger overestimations than the mild inclination (i.e. 4%) over longer distances (i.e. when the flag was at 3 m and 5 m), as expected according to the Economy of Action theory, this did not occur in the FM sample, for which no conclusive difference was observed.

Interestingly, in the HC group, visceral and neuropathic pain had an effect on participants’ perception of distances in the case of the farthest flag (i.e. 5m), indicating a direct relationship between overestimation errors and greater levels of visceral-neuropathic pain. It is worth noting that, while in the control group (and also in the FM group) musculoskeletal pain was sometimes reported as chronic (although localised and not as widespread as in the FM group, see Table SM5 and SM6), the same did not hold for visceral and neuropathic pain which was always reported as temporary in the HC group. Overall, the results suggest a difference in the impact of temporary compared to chronic and widespread pain on distance estimations. Furthermore, they suggest the possibility that the perception of bodily internal states (i.e. interoception) could impact space representation. Indeed, in this study, the predictions of the Embodied Perception Theory about the impact of pain on distance estimation were only confirmed in the case of temporary, but not chronic visceral or neuropathic pain. The overestimation of distances, which is consistent with higher metabolic costs relating to the effort of imagining actions, seems to be mainly associated with the moment-by-moment, perceived internal states of the body rather than with a stable condition of chronic musculoskeletal pain. Chronic, widespread pain induces a change in the cognitive strategies used to estimate distances, preventing the process of internal simulation of the movement to reach the target. Without this simulation, the task is carried out by means of visual strategies, with errors in estimations that are not influenced by distances and ramp inclination. These results provide evidence of the role of the current internal states of the body in space representation in the presence of chronic pain, thus supporting previous studies on healthy and deafferented groups (Beccherle et al., 2022; Scandola et al., 2020; Moro et al., 2023).

The effects of temporary pain on distance estimations

The results pertaining to the group of healthy participants support the Economy of Action hypothesis (Proffitt, 2006b). This theory claims that the perception that people have of their navigation space changes not only depending on variations in the characteristics of the environment but also on the current condition of their body. These factors affect their automatic, implicit estimate of the metabolic costs of moving within the environment. It has been hypothesised that this effect is advantageous from an evolutionary point of view since preserving metabolic energy might make a difference to an individual’s chance of survival (i.e. Economy of Action, Proffitt, 2006b). Previous studies have demonstrated that this body/space link is present not only when locomotory movements actually occur, but also when these movements are implicitly represented, as in the task used in the present study. For example, a series of experiments has shown that when people feel fatigued or physically unfit, they tend to overestimate slopes (Bhalla & Proffitt, 1999). The same happens with ageing or declining health (Bhalla & Proffitt, 1999). In contrast, motor expertise in sports or physical exercise influences and ameliorates a person’s visual perception of objects that have a crucial role in the sport they practise, for example, the hole in the course for golfers (Witt et al., 2008) or the ball for baseball players (Witt & Proffitt, 2005). Furthermore, temporary changes in bodily states may modulate space perception, as shown by the results of a seminal study which provided evidence that wearing a heavy backpack makes people perceive a target as being farther away than it is (Proffitt et al., 2003) and the inclination of a slope as steeper than in reality (Bhalla & Proffitt, 1999). The results of the HC group in this study confirm the effects of the inclination of the ramp on estimations of distance and suggest that transitory conditions of pain, in particular visceral and neuropathic pain (i.e. pain associated with internal states of the body), may modulate distance estimations.

Interestingly, there were no effects resulting from the position of the participants (i.e. sitting or standing) or other variables such as mood, thus excluding the possibility that participants’ anticipation regarding the expected responses was biased by the experimental paradigm or the response requests (Durgin et al., 2009; Schnall, 2017a; 2017b).

Two factors (which are not mutually exclusive) potentially explain the lack of difference related to the body position. The first possibility is that the two conditions do not differ in terms of the metabolic cost of the actions considered, and thus, asking participants to stand while executing the task is not enough to induce a sense of fatigue. The second possibility is that sitting does not impact the implicit mental representations of the actions required to move towards a target in the navigation space. This seems to be in contrast with a previous study (Scandola, Togni, et al., 2019) that compared the performance of a group of healthy subjects with a group of paraplegic participants using the same task described in this study. Paraplegia is a neurological condition associated with damage to the spinal cord leading to paralysis of the lower limbs (de-efferentation) and the absence of somatosensory information (de-afferentation) originating from the body parts below the lesion (Moro et al., 2022; Scandola, 2022). When sitting in their own wheelchair, the paraplegic participants estimated the distances with a pattern of overestimation that was extremely similar to that of the controls (i.e. increasing errors with greater distances), indicating the presence of an embodied simulation of the movement required to reach the target. However, when sitting in an unfamiliar wheelchair, they used only visual strategies and a different response pattern emerged (i.e. their errors did not change with the increase in distance). The data were interpreted in terms of embodiment since it appeared that the participants’ own wheelchairs had been embodied in their body representation (see the first experiment in Scandola, Togni, et al., 2019). As a consequence, to estimate distances, the paraplegic participants relied on motor representations when they were in their habitual condition (i.e. their own wheelchair) and a strategy involving only visual perception when they were in an unfamiliar wheelchair, which they found more difficult to maneuver. This evidence seems not to be confirmed by the present study, as the position does not impact the results. However, like the uncomfortable position in spinal cord injured people, also the presence of chronic pain prevents the internal simulation of movement potentially necessary to estimate distances in FM.

Chronic pain and navigation space

While the effects of temporary pain in undiagnosed participants support the Embodied Perception Theory, suggesting that a feeling of pain can turn into a cost for the body in terms of energy, chronic conditions of widespread pain do not seem to have similar effects. Indeed, the FM group did not overestimate distances like the control group, as the inclination of the ramp (with the steeper gradient implying a greater effort and cost to the body) did not affect their performance. This is an apparently counterintuitive result: indeed, while more severe pain was expected to be associated with more overestimation errors (Malfliet et al., 2017), the present study revealed that the severity of pain in the FM group did not impact on their performance.

One possible explanation for this peculiar result is related to the adaptation processes that come into play when the pain continues over time, with the consequence that several strategies are activated in order to deal with cognitive tasks (Scandola et al., 2017) and, among these, the estimation of distances that move from a motor toward a visual strategy. It may be that these adaptive processes are effective in warning the patients that engaging in a particular action might worsen the pain level, even though they may still, in any case, go ahead with the action execution.

It is well known that pain is a multidimensional experience that impacts the physiological and psychological states of individuals. Contrary to common belief, pain also involves cognitive processing and is not simply a sensory phenomenon, and as a result, it affects each individual differently (Casey & Lorenz, 2000). Previous studies have shown that chronic pain affects several aspects of cognition, such as attention (van der Leeuw et al., 2018), memory (Berryman et al., 2013), and decision making (Barnhart et al., 2019).

Moreover, pain also affects action representation and perception, and this supports the embodied cognition approach. In the Hand laterality task, images of left and right hands are shown in canonical or rotated positions on a computer screen, and participants are required to report hand laterality as fast and accurately as possible (Parsons, 1994). The reaction times collected in this experiment indicate a role of biomechanical constraints: in general, people performed better with non-rotated hands as compared to rotated hands, and reaction times became slower when the stimulus was shown at 180° of rotation. This suggests that the participants used a mental representation of their own hand rotating from 180° to 0° in order to identify the laterality of the hand on the screen (Parsons, 1994). Using the same task, Coslett and colleagues (2010) recorded slower reaction times in people suffering from chronic pain as compared to the controls, but only when the hands were rotated 180°. The authors concluded that a mental representation of hand rotation is more difficult for participants with chronic pain, reflecting the fact that it would, in effect, take longer for them to actually perform a rotation. This hypothesis is also supported by the results of studies with paraplegics, in which the biomechanical effect (i.e. the differences in response times to a hand or the foot in canonical or 180° rotated positions) is reduced only for images of feet as a consequence of deafferentation/deafferentation, even if the performance may ameliorate with motor rehabilitation (Scandola, Dodoni, et al., 2019). A dissociation between the visual perception of an action and the extraction of relative somatosensory information has been demonstrated in patients with chronic pain who accurately recognise the patterns of point-lights resembling biological motion but show significant impairment when asked to estimate the weight of invisible objects based on the point-light patterns they see. Crucially, this dissociation is only found when the movements shown involve painful body parts (De Lussanet et al., 2012). The differences with respect to the results from the task used in the present study are probably due to the localisation of symptoms that are specific to certain body parts as in these previous studies but are widespread in FM patients.

According to the Embodied Perception Theory, the representation of space and of action are intimately connected (Proffitt, 2006a) and it is reasonable to assume that chronic pain impacts the representation of the navigation space within which individuals imagine themselves moving. However, to date, it remains unclear whether chronic pain is associated with the metabolic cost of the action represented. Our results do not support this notion (but rather suggest a change from motor to visual strategy to carry out the task) and previous studies have also been unable to offer conclusive evidence (MacIntyre et al., 2022). Witt and colleagues (2009) used a distance perception task to compare a group of participants affected by chronic pain in their lower back and legs and a control group. Although the participant sample was small (8 participants suffering from pain and 7 healthy controls), the results indicate a general overestimation of distances in the group of patients suffering from chronic pain, but this did not apply to the controls. In contrast, a study with a larger sample (36 chronic pain sufferers with different diagnoses and 36 controls, Tabor et al., 2016) did not find any difference between the participants suffering from pain and the controls (MacIntyre et al., 2022). These inconsistent results might reflect not only the differences in the sample size, but also the heterogeneity of the nature and location of the pain (i.e. there were various locations and aetiologies in the study carried out by Tabor et al., 2016 and both lower back and leg pain in Witt et al., 2009). Our results extend previous evidence and also indicate a dissociation between temporary and widespread, chronic pain. Indeed, while the HC group was sensitive to the steeper ramps (with increasing overestimations), the FM group consistently increased their overestimation errors for farther distances, without being influenced by the inclination of the ramp. This behaviour is more consistent with a visual strategy rather than with motor simulation. According to the Economy of action hypothesis, it is possible to conclude that in the presence of temporary pain, people continue to estimate distances in an embodied way (with an internal simulation of a metabolic cost in the presence of inclined ramps), while chronic pain affects Embodied Perception.

Limitations

The empirical results reported herein should be considered in the light of some limitations. Some effects observed in experimental paradigms designed to test the Embodied Perception Theory might be influenced by the task requests. For example, Durgin and colleagues (2009, see also Firestone 2013 for a review) showed that Economy of Action effects might be explained in terms of participant bias (i.e. consciously or unconsciously acting in a way they believe the researcher wants them to, rather than responding naturally). However, if the task requests influenced participants in the current study, one should expect finding differences in the most obvious manipulated variable, which is the body position (i.e. Standing/Sitting), which indeed does not show any effects.

A further limitation is due to the impossibility of distinguishing between the effects of chronic pain and other features of FM disease. The comparison between FM and other patients suffering from chronic visceral-neuropathic pain (e.g. endometriosis or other organ diseases) is necessary to test the specific role of pain in Embodied Perception.

The results of this experimental study indicate a dissociation between the effects of localised, temporary pain and widespread, chronic pain in the estimation of distances. Transient neuropathic-visceral pain results in a body condition leading to implicit estimations of high energy costs associated with action representations (i.e. steeper ramps are associated with the perception of greater distances). More severe painful sensations are linked to a perceptual scaling of distances, as predicted by the Economy of Action hypothesis. Conversely, chronic pain seems to lead to relative insensitivity to conditions characterised by different metabolic costs. This might be explained by the presence of adaptive processes, or an impairment in the body-based estimation of the metabolic cost of an action. Although further studies are needed to explore the relationship between pain and Embodied perception, this study sheds new light on the cognitive effects of chronic and transient pain and how they might impact the perception of navigational space.

Author Contribution

M.S.: conceptualization; data curation; formal analysis; investigation; methodology; writing – original draft; writing – review and editing. M.B.: investigation; writing – original draft; writing – review and editing. E.P.: investigation. G.P.: investigation. E.R.: investigation. V.S.: conceptualization; methodology; project administration; resources; supervision; writing – review and editing. V.M.: conceptualization; funding acquisition; methodology; project administration; resources; supervision; writing – original draft; writing – review and editing.

Acknowledgement:

The study was supported by MIUR Italy (PRIN Edit. 2022, Prot. 20229JPNT7) to VM and MB.

Data Availability

Both the data and the script for the statistical analyses are available at: https://osf.io/fmys5/

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Pain and the Perception of Space in Fibromyalgia: Effects of Pain in Estimations of Distance

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Virtual reality scenarios

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Assessment of anxiety and depression

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The experimental Virtual Reality task: distance estimation

The effects of body positions on fatigue and pain

Effects of motor imagery and mood

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The effects of temporary pain on distance estimations

Chronic pain and navigation space

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