Doctors long believed that infants do not feel pain the way that older children and adults do. Instead, they believed that the infants' responses to discomfort were reflexes. Based on these beliefs, it was a routine practice to perform surgery on infants without suitable pain relief up until the late 1980s. Even now, infants may receive less than ideal pain relief. For example, a review found that although newborns in intensive care units undergo 11 painful procedures per day on average, more than half of the babies received no pain medications. Some guidelines continue to emphasize that for infants cuddling and feeding are more important sources of comfort than pain-relieving drugs.

There is growing support for better pain control for infants. Doctors and nurses now routinely observe behaviour and physiological responses—such as heart rate—to assess whether infants are experiencing pain. When an infant shows signs of pain, medical staff may give the infant sugar water or other interventions aimed at reducing their distress. However, recordings of brain activity suggest that infants may experience pain without exhibiting physical signs and that sugar water may reduce the behaviours associated with pain but not the pain itself.

More objective measurements of infant pain would be useful, but to create such measurements scientists must first understand how infants experience pain. So Goksan et al. used a technique called functional magnetic resonance imaging (fMRI) to compare the brain responses of adults and newborns to the same stimulus—a sharp poke of the foot. The adults were also asked about the pain they experienced, and whether the infants pulled their foot away when poked was documented.

The fMRI results revealed that pain increased activity in 20 regions in the adults' brains, and 18 of the same regions in the infants' brains. The brain regions activated in the infants' brains in response to a poke on the foot are involved in processing sensations and emotions. The two regions that did not activate in the infant brains—the amygdala and the orbitofrontal cortex—help individuals interpret the stimuli. Goksan et al. therefore conclude that infants experience pain in similar ways to adults, though they may not experience all the emotions that adults have when they are in pain. It is, therefore, important to give infants suitable pain relief during potentially painful procedures.

The network of brain regions that encode both the affective and sensory aspects of the pain experience have been well described in the adult (Apkarian et al., 2005; Tracey and Mantyh, 2007). It is not known which cortical and subcortical brain structures are activated following noxious events in infants. Early evidence demonstrated that infants exhibited reflex responses and concluded that pain was not processed at the level of the cortex (Rodkey and Pillai Riddell, 2013). This, coupled with an infant's inability to describe their pain experience verbally, led to extreme controversy regarding whether an infant has the ability to experience the unpleasant affective components of pain (Rodkey and Pillai Riddell, 2013). Consequently, infants have received poor pain management, exemplified during the 1980s by surgery being routinely performed using neuromuscular blocks without provision of adequate analgesia (Anand and Hickey, 1987). More recent research has primarily focussed on behavioural and physiological measures, which has led to the development of a number of infant pain assessment tools (Duhn and Medves, 2004). However, the lack of sensitivity and specificity of these measures means the trend to undertreat pain remains in clinical practice (Carbajal et al., 2008), despite concerted efforts to improve the management of pain in this population (Anand and International Evidence-Based Group for Neonatal Pain, 2001). For example, it is remarkable that current UK NHS guidelines for ankyloglossia (tongue tie) surgery state that ‘in small babies, being cuddled and fed are more important than painkillers’ (NHS Choices, 2015). Indeed, a recent review of neonatal pain management practice in intensive care highlighted that although infants experience an average of 11 painful procedures per day, 60% of the population did not receive any pharmacological analgesia (Roofthooft et al., 2014).

Recent studies using EEG and near-infrared spectroscopy have been used to provide reliable evidence that nociceptive information is transmitted to the newborn infant brain (Slater et al., 2006, 2010a, 2010b), and have highlighted the limitations of using observational behavioural measures to quantify pain in infants. For example, nociceptive information can be processed in the infant brain without a concomitant behavioural response (Slater et al., 2008), and interventions thought to alleviate pain (i.e., oral sucrose) can reduce clinical pain scores without reducing evoked nociceptive brain activity (Slater et al., 2010a). While these studies confirm that the infant central nervous system can process noxious stimulation, they do not elucidate the nature of the infant experience—in particular, which brain regions are involved, and therefore, whether the sensory, cognitive, and emotional aspects of pain are present in this population. Here, we identify the cortical and subcortical structures activated following acute noxious stimulation in the healthy newborn infant, and compare the activity with that observed in adults. The feasibility of this approach was demonstrated in a foundational pilot study (Williams et al., 2015). A case study in a single infant demonstrated that noxious stimulation evoked widespread brain activity (Williams et al. 2015), which included brain regions previously reported to be involved in adult pain (Tracey et al., 2007). Using a reverse inference approach to compare active brain regions in infants with those reported during adult pain, we postulate which aspects of the pain experience are present (Wager et al., 2013), providing an opportunity to gain insight into the organisation of nociceptive circuitry in the naïve infant brain.

In this study, acute noxious stimulation (PinPrick Stimulators, MRC Systems) was applied to the foot in both adults (n = 10; applied force: 32–512 mN) and infants (n = 10; applied force: 32–128 mN; greater force was not applied due to the potential risk of tissue damage). Using functional magnetic resonance imaging (fMRI) changes in blood oxygen level dependent (BOLD) activity in the brain were recorded in response to the stimuli. Adults were asked to verbally report their pain intensity and, using the McGill Pain questionnaire (Melzack and Torgerson, 1971), to describe the quality of the pain they experienced. As infants are unable to describe their pain, reflex leg withdrawal from the stimuli was visually observed during scanning. Parents were present during the studies and no infants were withdrawn from the study after recruitment.

Adult participants reported increased pain with increasing stimulus intensity (r = 0.48; p < 0.0001), and most frequently described the pain as pricking (n = 8 of 10) and sharp (n = 6 of 10). In infants, application of the stimuli evoked visible withdrawal of the stimulated leg, which could be observed at all stimulus intensities, whereas in adults, reflex withdrawal of the leg or foot was not observed at any stimulus intensity. While low threshold stimuli can also evoke reflex withdrawal in infants (Cornelissen et al., 2013), this observation confirms that the stimuli applied in this study were detected by the peripheral nervous system and transmitted to the central nervous system. Although noxious stimulation can elicit reflex limb withdrawal in adults, supraspinal modulation of the input means this activity is often suppressed in experimental studies.

In adults, noxious stimulation evoked significant increases in BOLD activity in cortical and subcortical brain regions, including primary somatosensory cortices, anterior cingulate cortex (ACC), bilateral thalamus, and all divisions of the insular cortices (Figure 1). All brain regions that had a significant increase in BOLD following noxious stimulation are identified in Table 1, and are consistent with previous literature (Tracey and Mantyh, 2007). In infants, the increases in BOLD activity evoked by the noxious stimulation were extremely similar to that seen in adults, and all but two of the 20 regions that were active in the adults were active in infants (Table 1 and Figure 1). While in adults the parietal lobe, pallidum, and precuneus cortex were only active in the brain regions contralateral to the site of stimulation, in infants these brain regions were also active on the ipsilateral side to the stimulus. Additional brain regions that were only active in the infants included the bilateral auditory cortices, hippocampus, and caudate (Table 1). The increased bilateral activity and greater number of active regions in infants are likely due to the immature cortico-cortical and interhemispheric pathways (Kostovic and Jovanov-Milosevic, 2006). Major reorganisation of the cortical circuitry occurs after the first postnatal month when there is a striking retraction of exuberant axons in the corpus callosum and there is a cessation of growth of the long cortico-cortical afferent pathways (Jovanov-Milosevic et al., 2006; Kostovic and Jovanov-Milosevic, 2006).

Figure 1

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Although the infant brain activity was widespread, the specificity of the response was demonstrated, as it was not present across all brain regions. For example, brain regions not commonly associated with the cerebral processing of nociceptive stimulation in the adult, such as the olfactory cortex, cuneus, and fusiform gyrus, were also not active in the infants. 14% of voxels across the whole brain were active following the application of the 128 mN stimuli in infants compared with 9% of voxels following the 512 mN stimuli in adults (Figure 2). In contrast, the 128 mN stimulus activated less than 1% of voxels in the adult brain. This demonstrates that the coverage and distribution of brain activity evoked by the 128 mN stimulus in infants was most similar to that evoked by the 512 mN stimulus in adults (Figure 2). This suggests that infants have increased sensitivity to nociceptive stimuli compared with adults, which is supported by previous data that show spinal nociceptive reflex withdrawal activity has greater amplitude and duration in infants compared with adults (Andrews and Fitzgerald, 1999; Skljarevski and Ramadan, 2002; Cornelissen et al., 2013). These data strongly imply that the threshold for evoking widespread nociceptive brain activity in infants is substantially lower than in adults. It is, however, not known whether the increased brain activity observed at a lower threshold in the infants is due to increased peripheral drive, for example due to differences in skin thickness between the adult and infant populations, or due to differences in transduction or subsequent central processing of the nociceptive input.

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Noxious stimulation in infants did not evoke activity in the amygdala or orbitofrontal cortex (OFC) (Table 1), and in contrast to the adults, where activity was present across all divisions of bilateral insular cortices, activity in the anterior division was not present (Figure 1). A recent white matter tractography study of the adult brain shows that the anterior insula has dominant connections with the OFC (Wiech et al., 2014). Based on many imaging studies spanning a range of stimuli and tasks, it is thought that activation in the anterior insula reflects the net evaluation of the affective impact of an impending situation. Similarly, the OFC is sensitive to stimuli with an emotional valence, however, it primarily responds to the reward value of the stimulus (including negative value) rather than its sensory features. Importantly, the OFC also encodes the anticipation of future outcomes, which makes it well suited for guiding subsequent decisions (Kahnt et al., 2010). It is likely that the infants are too immature and inexperienced to evaluate and contextualise the nociceptive stimulus into a coordinated decision and response, which might account for the lack of activity within these regions. Similarly, in adults the amygdala is thought to attach emotional significance to the nociceptive inputs it receives, and to play a role in fear and anxiety (Simons et al., 2014), which may reflect affective qualities that the newborn infant does not yet ascribe to the stimulus.

In light of these observations, it is plausible that infants do not experience the full range of aversive qualities that adults associate with nociceptive input. Indeed, this hypothesis is supported by evidence from rat pups, which shows that avoidance behaviour in a fear-conditioning paradigm does not manifest until postnatal day 10, and is associated with the enhancement of neural activity within the amygdala (Sullivan et al., 2000; Sullivan, 2001). Nevertheless, the observation that brain structures involved in affective processing, such as the anterior cingulate cortex, are activated following noxious stimulation suggests that infants do have the capacity to experience an emotionally relevant context related to incoming sensory input. Indeed, in adults the modulation of pain-related activity in the anterior cingulate cortex closely parallels a selective change in perceived unpleasantness (Rainville et al., 1997).

11 brain regions significantly encoded stimulus intensity in adults, whereas none of the active regions in infants exhibited significant intensity encoding (Table 1). Although the trend for intensity encoding in infants is clearly evident in some brain regions, these data suggest that infants do not discriminate stimulus intensity as well as adults (Figure 2—figure supplement 1). As only three stimulus intensities were applied to the infants it is plausible that if the intensity range were increased, significant intensity encoding may be observed. Nevertheless, when considering adult brain regions that did significantly intensity encode, three of the four highest ranked brain regions (ranked according to the degree of intensity encoding, and identified as the contralateral temporal gyri, opercular cortex, and all divisions of the insular cortex), were ranked in the same order within the top three regions in infants, highlighting the remarkable similarity in how the immature infant brain and adult brain encode nociceptive information (Table 1). Intensity encoding has been reported following low intensity von Frey hair stimulation (Williams et al., 2015).

Inferences about the subjective experience of pain are highly speculative, whether based on brain imaging data, behavioural responses or other autonomic or physiological observations. In most adults, where the pain experience can be communicated verbally, it is not always necessary to rely on surrogate measures when attempting to quantify an individual's pain experience or when assessing the need for analgesic provision. However, where verbal report is not possible as in the infant population or in those who are cognitively impaired, reliance on surrogate measures is essential when making inferences about pain perception. As cortical activation is a fundamental requirement for an experience to be interpreted as painful, inferences based on patterns of brain activity may provide the most reliable surrogate measure of pain compared with alternative approaches based on behavioural and physiological indicators that may not be reliably linked to central sensory or emotional processing in the brain (Oberlander et al., 2002; Ranger et al., 2007). This does not, however, negate the importance of taking a multidimensional approach to infant pain assessment by considering measures of brain activity in the context of other well-characterised behavioural and physiological indicators. Indeed, some researchers have argued that reverse inference based on brain imaging results should be used merely as a guide to direct further enquiry rather than a direct means to interpret results (Poldrack, 2008). Nevertheless, it has been shown using multivariate pattern analysis that pain-related brain activity can be classified and discriminated from other psychological states, suggesting a neural state for pain perception that is distinct from other sensory modalities and affective experiences (Yarkoni et al., 2011; Wager et al., 2013). Although we cannot necessarily infer an infant's subjective experience based on a given pattern of brain activity, these results make certain conclusions more likely. The closer the pattern of brain activity mimics activity observed in adults—who can report their subjective experience—the stronger the inference. The patterns of brain activity observed in this study make it likely that the infant experience is similar to that described by adults.

Pain is defined as an unpleasant sensory and emotional experience. This study provides the first demonstration that many of the brain regions that encode pain in adults are also active in full-term newborn infants within the first 7 days of life. This strongly supports the hypothesis that infants are able to experience both sensory and affective aspects of pain, and emphasizes the importance of effective clinical pain management.

1. 1. Anand KJ
   2. Hickey PR

   (1987) Pain and its effects in the human neonate and fetus

   The New England Journal of Medicine 317:1321–1329.

   https://doi.org/10.1056/NEJM198711193172105

   • Google Scholar
2. 1. Anand KJ
   2. International Evidence-Based Group for Neonatal Pain

   (2001) Consensus statement for the prevention and management of pain in the newborn

   Archives of pediatrics & adolescent medicine 155:173–180.

   https://doi.org/10.1001/archpedi.155.2.173

   • Google Scholar
3. 1. Andrews K
   2. Fitzgerald M

   (1999) Cutaneous flexion reflex in human neonates: a quantitative study of threshold and stimulus-response characteristics after single and repeated stimuli

   Developmental Medicine and Child Neurology 41:696–703.

   https://doi.org/10.1017/S0012162299001425

   • Google Scholar
4. 1. Apkarian AV
   2. Bushnell MC
   3. Treede RD
   4. Zubieta JK

   (2005) Human brain mechanisms of pain perception and regulation in health and disease

   European Journal of Pain 9:463–484.

   https://doi.org/10.1016/j.ejpain.2004.11.001

   • Google Scholar
5. 1. Arichi T
   2. Fagiolo G
   3. Varela M
   4. Melendez-Calderon A
   5. Allievi A
   6. Merchant N
   7. Tusor N
   8. Counsell SJ
   9. Burdet E
   10. Beckmann CF
   11. Edwards AD

   (2012) Development of BOLD signal hemodynamic responses in the human brain

   Neuroimage 63:663–673.

   https://doi.org/10.1016/j.neuroimage.2012.06.054

   • Google Scholar
6. 1. Carbajal R
   2. Rousset A
   3. Danan C
   4. Coquery S
   5. Nolent P
   6. Ducrocq S
   7. Saizou C
   8. Lapillonne A
   9. Granier M
   10. Durand P
   11. Lenclen R
   12. Coursol A
   13. Hubert P
   14. de Saint Blanquat L
   15. Boëlle PY
   16. Annequin D
   17. Cimerman P
   18. Anand KJ
   19. Bréart G

   (2008) Epidemiology and treatment of painful procedures in neonates in intensive care units

   JAMA 300:60–70.

   https://doi.org/10.1001/jama.300.1.60

   • Google Scholar
7. 1. Cornelissen L
   2. Fabrizi L
   3. Patten D
   4. Worley A
   5. Meek J
   6. Boyd S
   7. Slater R
   8. Fitzgerald M

   (2013) Postnatal temporal, spatial and modality tuning of nociceptive cutaneous flexion reflexes in human infants

   PLOS ONE 8:e76470.

   https://doi.org/10.1371/journal.pone.0076470

   • Google Scholar
8. 1. Desikan RS
   2. Segonne F
   3. Fischl B
   4. Quinn BT
   5. Dickerson BC
   6. Blacker D
   7. Buckner RL
   8. Dale AM
   9. Maguire RP
   10. Hyman BT
   11. Albert MS
   12. Killiany RJ

   (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest

   Neuroimage 31:968–980.

   https://doi.org/10.1016/j.neuroimage.2006.01.021

   • Google Scholar
9. 1. Duhn LJ
   2. Medves JM

   (2004) A systematic integrative review of infant pain assessment tools

   Advances in Neonatal Care 4:126–140.

   https://doi.org/10.1016/j.adnc.2004.04.005

   • Google Scholar
10. 1. Greve DN
    2. Fischl B

    (2009) Accurate and robust brain image alignment using boundary-based registration

    Neuroimage 48:63–72.

    https://doi.org/10.1016/j.neuroimage.2009.06.060

    • Google Scholar
11. 1. Jenkinson M
    2. Bannister P
    3. Brady M
    4. Smith S

    (2002) Improved optimization for the robust and accurate linear registration and motion correction of brain images

    Neuroimage 17:825–841.

    https://doi.org/10.1006/nimg.2002.1132

    • Google Scholar
12. 1. Jenkinson M
    2. Smith S

    (2001) A global optimisation method for robust affine registration of brain images

    Medical Image Analysis 5:143–156.

    https://doi.org/10.1016/S1361-8415(01)00036-6

    • Google Scholar
13. 1. Jovanov-Milosević N
    2. Benjak V
    3. Kostovic I

    (2006)

    Transient cellular structures in developing corpus callosum of the human brain

    Collegium Antropologicum 30:375–381.

    • Google Scholar
14. 1. Kahnt T
    2. Heinzle J
    3. Park SQ
    4. Haynes JD

    (2010) The neural code of reward anticipation in human orbitofrontal cortex

    Proceedings of the National Academy of Sciences of USA 107:6010–6015.

    https://doi.org/10.1073/pnas.0912838107

    • Google Scholar
15. 1. Kostovic I
    2. Jovanov-Milosevic N

    (2006) The development of cerebral connections during the first 20-45 weeks' gestation

    Seminars in Fetal & Neonatal Medicine 11:415–422.

    https://doi.org/10.1016/j.siny.2006.07.001

    • Google Scholar
16. 1. Melzack R
    2. Torgerson WS

    (1971)

    On the language of pain

    Anesthesiology 34:50–59.

    • Google Scholar
17. 1. NHS Choices

    (2015) Tongue tie

    Tongue tie, http://wwwnhsuk/conditions/tongue-tie/Pages/Introductionaspx.

    http://wwwnhsuk/conditions/tongue-tie/Pages/Introductionaspx

    • Google Scholar
18. 1. Oberlander TF
    2. Grunau RE
    3. Fitzgerald C
    4. Whitfield MF

    (2002) Does parenchymal brain injury affect biobehavioral pain responses in very low birth weight infants at 32 weeks' postconceptional age?

    Pediatrics 110:570–576.

    https://doi.org/10.1542/peds.110.3.570

    • Google Scholar
19. 1. Poldrack RA

    (2008) The role of fMRI in cognitive neuroscience: where do we stand?

    Current Opinion in Neurobiology 18:223–227.

    https://doi.org/10.1016/j.conb.2008.07.006

    • Google Scholar
20. 1. Rainville P
    2. Duncan GH
    3. Price DD
    4. Carrier B
    5. Bushnell MC

    (1997) Pain affect encoded in human anterior cingulate but not somatosensory cortex

    Science 277:968–971.

    https://doi.org/10.1126/science.277.5328.968

    • Google Scholar
21. 1. Ranger M
    2. Johnston CC
    3. Anand KJ

    (2007) Current controversies regarding pain assessment in neonates

    Seminars in Perinatology 31:283–288.

    https://doi.org/10.1053/j.semperi.2007.07.003

    • Google Scholar
22. 1. Rodkey EN
    2. Pillai Riddell R

    (2013) The infancy of infant pain research: the experimental origins of infant pain denial

    The Journal of Pain 14:338–350.

    https://doi.org/10.1016/j.jpain.2012.12.017

    • Google Scholar
23. 1. Roofthooft DW
    2. Simons SH
    3. Anand KJ
    4. Tibboel D
    5. van Dijk M

    (2014) Eight years later, are we still hurting newborn infants?

    Neonatology 105:218–226.

    https://doi.org/10.1159/000357207

    • Google Scholar
24. 1. Serag A
    2. Aljabar P
    3. Ball G
    4. Counsell SJ
    5. Boardman JP
    6. Rutherford MA
    7. Edwards AD
    8. Hajnal JV
    9. Rueckert D

    (2012) Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression

    Neuroimage 59:2255–2265.

    https://doi.org/10.1016/j.neuroimage.2011.09.062

    • Google Scholar
25. 1. Shi F
    2. Yap PT
    3. Wu G
    4. Jia H
    5. Gilmore JH
    6. Lin W
    7. Shen D

    (2011) Infant brain atlases from neonates to 1- and 2-year-olds

    PLOS ONE 6:e18746.

    https://doi.org/10.1371/journal.pone.0018746

    • Google Scholar
26. 1. Simons LE
    2. Moulton EA
    3. Linnman C
    4. Carpino E
    5. Becerra L
    6. Borsook D

    (2014) The human amygdala and pain: evidence from neuroimaging

    Human Brain Mapping 35:527–538.

    https://doi.org/10.1002/hbm.22199

    • Google Scholar
27. 1. Skljarevski V
    2. Ramadan NM

    (2002) The nociceptive flexion reflex in humans – review article

    Pain 96:3–8.

    https://doi.org/10.1016/S0304-3959(02)00018-0

    • Google Scholar
28. 1. Slater R
    2. Cantarella A
    3. Franck L
    4. Meek J
    5. Fitzgerald M

    (2008) How well do clinical pain assessment tools reflect pain in infants?

    PLOS Medicine 5:e129.

    https://doi.org/10.1371/journal.pmed.0050129

    • Google Scholar
29. 1. Slater R
    2. Cantarella A
    3. Gallella S
    4. Worley A
    5. Boyd S
    6. Meek J
    7. Fitzgerald M

    (2006) Cortical pain responses in human infants

    The Journal of neuroscience 26:3662–3666.

    https://doi.org/10.1523/JNEUROSCI.0348-06.2006

    • Google Scholar
30. 1. Slater R
    2. Cornelissen L
    3. Fabrizi L
    4. Patten D
    5. Yoxen J
    6. Worley A
    7. Boyd S
    8. Meek J
    9. Fitzgerald M

    (2010a) Oral sucrose as an analgesic drug for procedural pain in newborn infants: a randomised controlled trial

    Lancet 376:1225–1232.

    https://doi.org/10.1016/S0140-6736(10)61303-7

    • Google Scholar
31. 1. Slater R
    2. Worley A
    3. Fabrizi L
    4. Roberts S
    5. Meek J
    6. Boyd S
    7. Fitzgerald M

    (2010b) Evoked potentials generated by noxious stimulation in the human infant brain

    European Journal of Pain 14:321–326.

    https://doi.org/10.1016/j.ejpain.2009.05.005

    • Google Scholar
32. 1. Smith SM

    (2002) Fast robust automated brain extraction

    Human Brain Mapping 17:143–155.

    https://doi.org/10.1002/hbm.10062

    • Google Scholar
33. 1. Sullivan RM

    (2001) Unique characteristics of neonatal classical conditioning: the role of the amygdala and locus coeruleus

    Integrative Physiological and Behavioral Science 36:293–307.

    https://doi.org/10.1007/BF02688797

    • Google Scholar
34. 1. Sullivan RM
    2. Landers M
    3. Yeaman B
    4. Wilson DA

    (2000) Good memories of bad events in infancy

    Nature 407:38–39.

    https://doi.org/10.1038/35024156

    • Google Scholar
35. 1. Thesen S
    2. Heid O
    3. Mueller E
    4. Schad LR

    (2000) Prospective acquisition correction for head motion with image-based tracking for real-time fMRI

    Magnetic Resonance in Medicine 44:457–465.

    https://doi.org/10.1002/1522-2594(200009)44:3<457::AID-MRM17>3.0.CO;2-R

    • Google Scholar
36. 1. Tracey I
    2. Mantyh PW

    (2007) The cerebral signature for pain perception and its modulation

    Neuron 55:377–391.

    https://doi.org/10.1016/j.neuron.2007.07.012

    • Google Scholar
37. 1. Wager TD
    2. Atlas LY
    3. Lindquist MA
    4. Roy M
    5. Woo CW
    6. Kross E

    (2013) An fMRI-based neurologic signature of physical pain

    The New England Journal of Medicine 368:1388–1397.

    https://doi.org/10.1056/NEJMoa1204471

    • Google Scholar
38. 1. Wiech K
    2. Jbabdi S
    3. Lin CS
    4. Andersson J
    5. Tracey I

    (2014) Differential structural and resting state connectivity between insular subdivisions and other pain-related brain regions

    Pain 155:2047–2055.

    https://doi.org/10.1016/j.pain.2014.07.009

    • Google Scholar
39. 1. Williams G
    2. Fabrizi L
    3. Meek J
    4. Jackson D
    5. Tracey I
    6. Robertson N
    7. Slater R
    8. Fitzgerald M

    (2015) Functional magnetic resonance imaging can be used to explore tactile and nociceptive processing in the infant brain

    Acta Paediatrica 104:158–166.

    https://doi.org/10.1111/apa.12848

    • Google Scholar
40. 1. Woolrich MW
    2. Jbabdi S
    3. Patenaude B
    4. Chappell M
    5. Makni S
    6. Behrens T
    7. Beckmann C
    8. Jenkinson M
    9. Smith SM

    (2009) Bayesian analysis of neuroimaging data in FSL

    Neuroimage 45:S173–S186.

    https://doi.org/10.1016/j.neuroimage.2008.10.055

    • Google Scholar
41. 1. Yarkoni T
    2. Poldrack RA
    3. Nichols TE
    4. Van Essen DC
    5. Wager TD

    (2011) Large-scale automated synthesis of human functional neuroimaging data

    Nature Methods 8:665–670.

    https://doi.org/10.1038/nmeth.1635

    • Google Scholar

Author details

1. Sezgi Goksan

   Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

   Contribution

   SG, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

2. Caroline Hartley

   Department of Paediatrics, University of Oxford, Oxford, United Kingdom

   Contribution

   CH, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-7981-0836

3. Faith Emery

   Department of Paediatrics, University of Oxford, Oxford, United Kingdom

   Contribution

   FE, Conception and design, Acquisition of data

   Competing interests

   The authors declare that no competing interests exist.

4. Naomi Cockrill

   Department of Paediatrics, University of Oxford, Oxford, United Kingdom

   Contribution

   NC, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

5. Ravi Poorun

   Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

   Contribution

   RP, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

6. Fiona Moultrie

   Department of Paediatrics, University of Oxford, Oxford, United Kingdom

   Contribution

   FM, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

7. Richard Rogers

   Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

   Contribution

   RR, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

8. Jon Campbell

   Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

   Contribution

   JC, Acquisition of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

9. Michael Sanders

   Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

   Contribution

   MS, Acquisition of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

10. Eleri Adams

    Department of Paediatrics, University of Oxford, Oxford, United Kingdom

    Contribution

    EA, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

11. Stuart Clare

    Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

    Contribution

    SC, Conception and design, Acquisition of data, Analysis and interpretation of data

    Competing interests

    The authors declare that no competing interests exist.

12. Mark Jenkinson

    Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

    Contribution

    MJ, Acquisition of data, Analysis and interpretation of data

    Competing interests

    The authors declare that no competing interests exist.

13. Irene Tracey

    Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

    Contribution

    IT, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

14. Rebeccah Slater

    1. Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    2. Department of Paediatrics, University of Oxford, Oxford, United Kingdom

    Contribution

    RS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    For correspondence

    rebeccah.slater@paediatrics.ox.ac.uk

    Competing interests

    The authors declare that no competing interests exist.

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