Cortical representation of experimental tooth pain in humans

Pain 118 (2005) 390–399 www.elsevier.com/locate/pain

Cortical representation of experimental tooth pain in humans H.H.F. Jantscha, P. Kemppainenb,c, R. Ringlera, H.O. Handwerkera, C. Forstera,* a

Department of Physiology and Pathophysiology, University of Erlangen-Nuernberg, Universitaetsstrasse 17, D-91054 Erlangen, Germany b Institute of Dentistry, University of Helsinki, Finland c Finnish Student Health Service, Helsinki, Finland Received 20 January 2005; received in revised form 25 August 2005; accepted 12 September 2005

Abstract Cortical processing of electrically induced pain from the tooth pulp was studied in healthy volunteers with fMRI. In a first experiment, cortical representation of tooth pain was compared with that of painful mechanical stimulation to the hand. The contralateral S1 cortex was activated during painful mechanical stimulation of the hand, whereas tooth pain lead to bilateral activation of S1. The S2 and insular region were bilaterally activated by both stimuli. In S2, the center of gravity of the activation during painful mechanical stimulation was more medial/posterior compared to tooth pain. In the insular region, tooth pain induced a stronger activation of the anterior and medial parts. The posterior part of the anterior cingulate gyrus was more strongly activated by painful stimulation of the hand. Differential activations were also found in motor and frontal areas including the orbital frontal cortex where tooth pain lead to greater activations. In a second experiment, we compared the effect of weak with strong tooth pain. A significantly greater activation by more painful tooth stimuli was found in most of those areas in which tooth pain had induced more activation than hand pain. In the medial frontal and right superior frontal gyri, we found an inverse relationship between pain intensity and BOLD contrast. We concluded that tooth pain activates a cortical network which is in several respects different from that activated by painful mechanical stimulation of the hand, not only in the somatotopically organized somatosensory areas but also in parts of the ‘medial’ pain projection system. q 2005 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. Keywords: Cortical mapping; fMRI; Pain intensity; Somatotopic representation; Trigeminal system; Tooth pain

1. Introduction There are numerous studies on the activation of the cerebral cortex by experimental painful stimulation using methods of functional brain imaging (MEG, PET, fMRI) (for review see Peyron et al., 2002; Treede et al., 1999). In most cases, stimuli have been applied to the upper extremity and either heat (Becerra et al., 2001; Davis, 2000; Tracey et al., 2000) or more rarely mechanical stimulation (Disbrow et al., 1998; Forster et al., 2000) served for inducing pain. There is general agreement that painful stimulation excites a cortical network consisting of neuronal clusters in both hemispheres. Other body

* Corresponding author. Tel.: C49 91318522492; fax: C49 91318522497. E-mail address: [email protected] (C. Forster).

areas and other types of painful stimulation have rarely been used for those studies. Little is known about the representation of pain of trigeminal origin, and in particular of tooth pain. A recent study reported that non-painful dental mechanical stimulation provoked bilateral activation of the insular cortex (IC), but only a rare activation of S1 (Ettlin et al., 2004). This raises the question whether this is also true for nociceptive input from the trigeminal regions, in particular for painful stimulation of the tooth pulp. This is interesting for several reasons: The tooth pulp is innervated almost exclusively by nociceptive afferents and therefore, tooth stimulation may provide selective nociceptive input (Byers and Narhi, 1999). Indeed, electrical tooth stimulation has been widely used for studying experimental trigeminal pain in humans (Kemppainen et al., 1985; 2001; 2003). Pathological pain states in the trigeminal region are strikingly different from pain in

0304-3959/$20.00 q 2005 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.pain.2005.09.017

H.H.F. Jantsch et al. / Pain 118 (2005) 390–399

other regions. Tooth pain has been regarded as kind of visceral pain rather than ‘surface pain’ from the skin. The purpose of this investigation was to explore by fMRI the cortical processing of tooth pain in comparison to pain induced in the hand. Relevant cortical areas that were responsive to electrically induced tooth pain were studied, and the fMRI-responses were compared to those induced by phasic mechanical stimulation of a hand as employed in our earlier studies (Ringler et al., 2003).

2. Methods 2.1. Subjects Eight healthy volunteers (four male, four female, aged 21–28) took part in this study. The study was approved by the local ethics committee. All volunteers gave their written informed consent to participate. Each subject underwent a training session. Its purpose was to make the subjects familiar with the stimulation procedure and to adjust the stimulus strengths in both stimulus modalities to levels of approximately equal painfulness. For these measurements, the subjects sat reclined in a dental chair and stimuli were applied as in the fMRI sessions. The rating procedure was also identical: They operated a visual analogue scale with a turning knob. Blood pressure and heart rate were continuously recorded (Ohmeda FinaPressw) and peripheral skin blood flow in the stimulated hand was measured by laser Doppler flowmetry as we did in previous studies (Kemppainen et al., 2001).

391

1982). These findings indicate that only intra-pulpal afferent fibers were activated during tooth stimulation in the present study. The current consisted of constant current pulses of 10 ms duration at a frequency of 5 Hz, which should activate pulpal Ad and C-fibers at liminal perceptual intensities (Narhi, 1985; Narhi et al., 1982; Virtanen, 1985; Virtanen et al., 1987). 2.3. Experimental protocol Training and fMRI sessions consisted of two experiments. In the first experiment, we applied alternatively mechanical finger stimuli and electrical tooth pain (HT, hand-tooth sequence). The experiment lasted 375 s. The first period of hand stimulation started after 20 s of baseline and lasted 20 s. It was immediately followed by tooth pulp stimulation which also lasted 20 s (see Fig. 1). After a 15 s resting period a reversed stimulus sequence (first tooth then hand stimulation) followed. Six stimulus sequences (alternating finger-tooth and toothfinger) were performed according to this scheme. During all stimulations the subjects rated their pain level on a visual analogue scale which they operated by a turning knob (diameter 4 cm) with the index finger of their right hand. The rating scale represented 0–100% (no pain to maximal bearable pain). During hand and tooth stimulation, the stimulus strength was continuously adapted by the experimenter to achieve a pain rating around 60%. The subject was not aware of these stimulus manipulations. The stimuli were applied to the left hand and to the upper left first incisor. The second experiment followed an identical protocol, but instead of the hand stimulation another electrical tooth stimulation was applied and its intensity adjusted to get a rating level of 30% (TWS, tooth weak strong) (see Fig. 1). 2.4. MR imaging

2.2. Stimulation procedure A pneumatically driven impact stimulator was used for painful mechanical stimulation of the hand. The stimulator was designed without ferromagnetic components for use close to the MR scanner. This stimulator was previously described in detail (Kohlloeffel et al., 1991). In short, a cylindrical plastic bullet (diameter: 5 mm; mass: 0.5 g) was accelerated through a guiding barrel and shot to the back of the middle phalanx with a repetition rate of 1 Hz. This gave 15 impacts per stimulation period, the velocity immediately before the impact was 10–15 m/s. The dental stimulation was generated with a constant current tooth stimulator as described previously (Kemppainen et al., 1985). In order to prevent induction of electrical currents by the high magnetic fields in the MR scanner, the lead between the tooth electrode and the stimulus amplifier was designed from carbon wire. The cathode of the stimulator was glued to the intact upper left first incisor. The other electrode was fixed to the lower leg. The cathode was covered with insulating material to prevent a connection between the cathode and extrapulpal tissues. The electrode impedance of the stimulated teeth was monitored throughout the experiments, and it was between 2.9 and 4.2 MU, confirming that there was no short-circuiting to periodontal tissues. Moreover, electrophysiological evidence indicates that the maximal strength (below 60 mA) of the electrical current used in this study for dental stimulation, even when applied to periodontium, does not activate extra-pulpal nerve fibers (Na¨rhi et al.,

The head of the subject was fixed in the scanner by rubber pads and the ears were plugged. A mirror was adjusted above the eyes to allow the subject to see the visual analogue scale positioned outside of the scanner. Imaging was performed with an 1.5 T Sonata MRI scanner (Siemens, Erlangen, Germany). A magnetization prepared rapid gradient echo (MPRAGE) sequence was recorded consisting of 160 sagital slices of 1 mm thickness and an in-plane resolution of 256!256 pixel (field of view: 220!220 mm2). Functional T2* A HP: Hand pain vs. tooth pain

0

60

120

180

240

300

360

[sec]

240

300

360

[sec]

B TWS: weak vs. strong tooth pain

0

60

120

HP = hand pain TP = tooth pain (

180

weak,

strong)

Fig. 1. Stimulation protocol: (A) hand pain vs. tooth pain (HT); (B) weak vs. strong tooth pain (TWS). During HT a block of finger stimulation was followed immediately by a block of tooth stimulation and after a resting period, vice versa. This scheme was repeated three times. During TWS, the same protocol was used, however, weak tooth pain was applied instead of finger pain.

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weighted images were obtained using an EPI (echo planar imaging) technique consisting of 16 axial slices (TRZ3000 ms, TEZ60 ms, flip angleZ908, slice timeZ100 ms per block of 16 slices, slice thicknessZ4 mm, field of view 220!220 mm2, 128!128 pixel). Possible head movements of the subjects were corrected online using the prospective acquisition correction of the scanner software (Thesen et al., 2000). 2.5. Data analysis and statistics Psychophysical data were recorded and analyzed with custom made software. Analysis of the fMRI data was performed using BrainVoyagerw 2000 (Brain Innovations, Netherlands, www. brainvoyager.com) with motion correction, temporal Gaussian smoothing of 4 s; spatial Gaussian smoothing of 4 mm; linear

detrending; General Linear Model (GLM) was used for detecting activated brain areas. The factors used for the GLM model were the stimulation modality or stimulation intensity, respectively. Covariates were used to account for the effects of the order of stimulation (finger-tooth or tooth-finger, see Fig. 1) and the individual rating movements. A clustering algorithm was used so that a brain site was only regarded as activated, when a cluster size of at least 150 mm3 showed above-threshold correlation coefficients (Ringler et al., 2003). For displaying the activated clusters at different brain sites the functional images were co-registered with the 3D MPRAGE data set using the according routines of BrainVoyager. The resulting transformations were used to overlay the activation maps into a 3D data set. The affected brain areas were identified by comparing their location with a printed atlas (Damasio, 1995). If this comparison revealed clusters in the brain

Fig. 2. Activation map comparing finger and strong tooth pulp stimulation. (A) The result of the group analysis is projected onto the surface reconstruction of a single brain after Talairach transformation. The left side shows a superior view of the brain, the right side shows a lateral aspect of the right hemisphere. (B) Activation map shown in coronal slices. The numbers denote the y-coordinate of the according coronal slice in the Talairach space. Color coding in A and B: blue–green clusters: higher changes in the BOLD signal during painful mechanical finger stimulation as compared to tooth pulp stimulation, red–yellow clusters: higher changes during tooth pulp stimulation. Orientation: A, anterior; P, posterior; R, right; L, left.(For interpretation of the reference to colour in this legend, the reader is referred to the web version of this article)

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regions of interest, then the respective cluster was included in the subsequent statistical analysis and its size and the maximum fMRI response were determined. For group analysis, all functional data were transformed into Talairach space and a General Linear Model (GLM) was calculated to test for brain areas showing significant activations during the different stimulations. Group analyses were performed separately on each of the two experiments and then contrasts were calculated between the two different treatment conditions (hand vs. tooth pain and weak vs. strong tooth pain) using Brain Voyagers multi-subject statistical contrast parameters. Activations due to the rating movements were not considered in this study. The t-values obtained from

393

the GLM were used to compare the activation patterns. P!0.05 was regarded to be significant.

3. Results The average current strengths needed for weak and strong tooth stimuli were 23.0 mAG1.52 (meanGSEM) and 38.1 mAG2.27, respectively, to obtain a rating of 30 and 60%. Thus, the weak tooth stimulation was in the A–d activation range, whereas strong tooth stimulation activated also pulpal C afferent fibers (Narhi, 1985;

Table 1 Activated brain areas during hand vs. tooth pain Brain region

Single subject analysis

Group analysis

Subjects

t-values

Total S1 Face-area, left 6 Hand-area, right 6 Face-area, right 6 S2 Medial/posterior, left 4 Lateral/anterior, left 5 Medial/posterior, right 7 Lateral/anterior, right 6 Insular cortex Anterior, left 6 Medial, left 5 Posterior, left 3 Anterior, right – Medial, right 5 Posterior, right 6 Anterior cingulate cortex (ACC) Anterior, left – Posterior, left 7 Posterior, right 6 Precentral gyrus Face-area, left 5 Hand-area, right 6 Face-area, right – Orbital gyrus Left 6 Right 7 Inferior frontal gyrus Left 7 Right 8 Medial frontal gyrus Left 4 Right 7 Superior frontal gyrus Left 7 Right 7

H

T

H

2 4 2

5 2 6

7.31 3.81 7.44

4 0 7 0

0 5 0 6

2 1 2 – 2 5

P-values T

C

H

4.75 1.77 3.74

K2.82 K2.28 K4.14

9.50 3.97 8.97 5.41

5.74 9.58 3.77 10.66

4 4 2 – 3 2

2.63 3.69 3.11 – 5.11 7.01

5.34 5.75 5.63

– 7 5

– 5 5

– 4.61 5.80

1 4 –

5 4 –

2.73 3.45 –

4 5

5 4

4.34 2.82

3 3

7 7

2 4 5 6

Talairach coordinates T

C

x

y

z

!0.0001 !0.0001 0.0049 0.0001 0.0771 0.0226 !0.0001 0.0002 !0.0001

K59 25 55

K19 K39 K23

19 57 21

K4.17 6.61 K5.85 6.22

!0.0001 !0.0001 !0.0001 0.0001 !0.0001 !0.0001 !0.0001 0.0002 !0.0001 !0.0001 !0.0001 !0.0001

K57 K56 52 54

K26 K7 K23 K5

19 19 16 16

3.21 2.47 3.00

K30 K36 K33 – 36 34

15 0 K6 – K7 K25

6 5 16 – 18 18

8.56 2.76

4.12 K4.79

0.0086 !0.0001 0.0014 0.0002 !0.0001 0.0136 0.0019 !0.0001 0.0028 – – – !0.0001 !0.0001 !0.0001 !0.0001 0.0059 !0.0001

2.14 3.51

– K2.76 K2.54

– – – !0.0001 0.0323 0.0059 !0.0001 0.0005 0.0114

– K1 2

– K5 K16

– 37 42

8.51 7.05

6.78 4.25

K57 47 –

0 0

–

0.0065 !0.0001 !0.0001 0.0006 !0.0001 !0.0001 – – –

22 47 –

2.23 0.59

K2.36 K2.53

!0.0001 0.0050

4.17 3.51

7.28 6.16

3 6

3.65 2.05

5 3

5.03 4.91

–

–

–

–

–

0.0260 0.5566

0.0183 0.0116

K20 9

55 64

9 13

3.71 3.15

!0.0001 !0.0001 0.0005 !0.0001

0.0002 0.0017

K46 46

31 23

17 17

6.74 5.21

3.67 3.72

0.0003 !0.0001 0.0406 !0.0001

0.0003 0.0002

K46 35

33 45

17 35

2.29 7.31

K3.07 2.90

!0.0001 0.0220 !0.0001 !0.0001

0.0022 0.0038

K28 19

52 58

34 13

Results of the single subject and group analysis of the HT experiment in the different brain regions. The columns ‘number of subjects’ show the number of subjects in whom activation was found by the single subject analysis. The numbers are given separately for both stimuli (total), hand pain (H) and tooth pain (T). The next columns show the t-values and their P-values as obtained by the general linear model (GLM), which was used for the group analysis. They are given separately for hand pain (H), tooth pain (T) and for the contrast (C). Positive t-values for contrasts represent higher BOLD changes during tooth stimulation as compared with hand stimulation and vice versa for negative t-values. All significant t-values are printed in bold. The Talairach coordinate denote the center of gravity of the cluster as found by the group analysis.

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Virtanen, 1985). In two subjects, the stimulus strength had to be slightly increased during each stimulus block and it had to be 10 mA higher during the 6th compared to the 1st stimulus block. The impact stimuli to the left hand had to be adjusted to a velocity of 10–15 m/s to achieve a rating of 60%. In three subjects, the velocity had to be increased by as much as 3 m/s to maintain this rating level. During the stimulation periods, the ratings did not change much. Therefore, only few movements were necessary to be done by the subjects. No subject reported sensations during the resting periods (pain rating 0%). Blood pressure increased in the beginning of the stimuli while heart rate decreased. Blood flow through the skin of the stimulated hand decreased during painful stimulation in agreement with previous studies (Kemppainen et al., 2001). After both the training and fMRI sessions, the subjects reported that the tooth pulp stimulus was more unpleasant in the beginning of a stimulus sequence whereas the hand pain became more unpleasant towards the end.

Also in the frontal cortical areas differential activation was found. Tooth pain was bilaterally more effective in the inferior and medial frontal gyrus, as well as in the contralateral superior frontal gyrus, whereas hand pain induced greater BOLD responses in the ipsilateral superior frontal gyrus and bilaterally in the orbital cortex. From Table 1, it can also be seen to what extent the results from the eight subjects obtained in single-subject analysis contributed to the results of the group analysis. Fig. 3 shows the time course of the average activations during the ‘hand vs. tooth pain’ (HT) session in four brain areas: the ipsi- and contralateral oral projection field in S1 1.2 0.8

S1 ipsi, trigeminal region

B

S1 contra, trigeminal region

0.4 0 -0.4 1.2

3.1. Cortical activations

0.8 0.4 Change of BOLD signal (%)

3.1.1. Comparison of finger vs. tooth pulp stimulation The results of the ‘hand vs. tooth pain’ (HT sequence) experiment are shown in Fig. 2. In this experiment, activations by tooth and hand pain were encountered in projection areas S1 and S2, the insular cortex, the anterior cingulate cortex, motor cortex and frontal areas, including the orbital cortex. The most powerful activations were found in the S2 projection area with the highest t-values for hand (center of gravity in the medial/posterior part, tZ9.50 left hemisphere, tZ8.97, right hemisphere) and tooth stimulation (center of gravity in the lateral/anterior part, tZ9.58 left hemisphere, tZ10.66, right hemisphere). Table 1 summarizes the activations found during this experiment including the contrasts. In the latter, a positive t-value indicates stronger activations during tooth pain while a negative value denotes stronger activations during painful mechanical hand stimulation. Tooth pain was more effective in the right and left lateral/anterior parts of S2. In contrast, hand pain induced stronger BOLD changes bilaterally in the medial/posterior parts of S2, in the contralateral S1 area, but interestingly also bilaterally in the face area of S1. The insular cortex was bilaterally activated by both stimulus and pain modalities. A more detailed analysis of the contrasts showed differences in the anterior, medial and posterior parts of this brain region. Except for the posterior contralateral insular cortex tooth pain induced stronger BOLD responses than impact stimulation of the hand. A strong BOLD response was found in the left, ipsilateral precentral gyrus (M1), which was significantly higher during tooth stimulation.

A

0 -0.4 1.2 C

0,8 0.4 0

S2 ipsi, lateral part

-0.4 1.2 D

0.8 0.4 0

S2 ipsi, medial part

-0.4 0

80

160

240

320

400

time (sec) resting period finger pain tooth pain Fig. 3. Time course of BOLD-signals in S1 and S2 areas during the HT experiment. The courses of the signals were subdivided into 19 segments, each lasting 21 s. The mean value of these segments were used to calculated the BOLD changes shown in this plot. (A) S1 ipsilateral (left hemisphere), face area; (B) S1 contralateral (right hemisphere), face area; (C) lateral/anterior part of the ipsilateral S2 area; (D) medial/posterior part of the ipsilateral S2 area.

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395

Fig. 4. Activation map comparing weak and strong tooth pulp stimulation. The result of the group analysis is projected onto a single brain after Talairach transformation. The numbers denote the y-coordinate of the according coronal slice in the Talairach space. Color coding: blue–green cluster: higher changes in the BOLD signal during weak tooth stimulation as compared to strong tooth pulp stimulation, red–yellow clusters: higher changes during strong tooth pulp stimulation. (For interpretation of the reference to colour in this legend, the reader is referred to the web version of this article).

and the ipsilateral lateral/anterior and medial/posterior portion of S2. 3.1.2. Comparison of weak vs. strong tooth pain This experiment (TWS sequence) was designed to explore in which of the various activated areas BOLD effects were quantitatively related to the intensity of tooth pain. Stimuli rated as 30% were compared with those rated as 60% of the rating scale. The results are shown in Fig. 4 and summarized in Table 2. Group analysis detected only activation in the left, ipsilateral face area of S1, whereas no significant clusters formed in the contralateral face area of S1. Pain intensity was apparently coded in the left face area. In S2, significant intensity coding was bilateral in the lateral/anterior part, in agreement with the results of the HT sequence in which tooth pain induced a stronger response compared to hand pain in lateral S2 (Fig. 5). In the insular cortex (IC), the strongest activations were found in the left medial and posterior parts. Both regions apparently coded the stimulus intensity. In the right IC, only the medial part showed intensity coding. The anterior and posterior part of the left anterior cingulate cortex (ACC) showed larger responses to strong tooth stimulation. Interestingly, the right posterior part of the ACC was only activated by the weak tooth stimulus (see Table 2). In the precentral gyrus, intensity coding was observed in the face areas of both hemispheres. Surprisingly, also the right hand area showed higher t-values by the strong tooth pain. Particularly, interesting are the results from the frontal areas. Medial and superior frontal gyrus showed a clear inverse coding of tooth pain intensity, but generally a stronger response to tooth compared to hand pain. Only in the left superior frontal gyrus tooth pain induced weaker responses and the intensity coding was inverse. In most

cases, coding of tooth pain intensity was observed in those cortical areas in which tooth stimulation lead to larger responses than painful mechanical hand stimulation. However, there were a few remarkable exceptions: The anterior left insular cortex was stronger activated by tooth, but showed no significant response in the TWS experiment, in the right face area of the precentral gyrus it was the other way around: no significant response in the first experiment, but intensity coding in the TWS experiment.

4. Discussion The present results reveal that tooth and hand pain of similar intensity activate similar cortical networks, albeit with characteristic differences. Not surprisingly, hand pain induced a strong activation in the contralateral hand area of the somatotopically organized S1 area. Tooth stimulation activated the S1 face area bilaterally, while hand stimulation activated S1 only contralaterally. In addition, mechanical hand stimulation leads to a stronger BOLD effect even in the face area. This dominant activation of the S1 projection field by hand stimulation may be related to the mechanical nature of the hand pain stimulus used which—in addition to nociceptors—also excited myelinated mechanoreceptors in the skin. Though we have shown in a previous study that painful mechanical stimulation of the hand lead to weaker S1 activation compared to non-painful stimuli (Ringler et al., 2003), the mechanoreceptor input might still be dominant in this area over the nociceptor input. The tooth pulp stimulation provided a purely nociceptive input to S1. The bilateral S1 activation during tooth stimulation is probably not due to a bilateral innervations of the left upper incisor tooth used for stimulation since we have recently shown in a study on capsaicin-induced axon

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Table 2 Activated brain areas during weak and strong tooth pain Brain region

Single subject analysis Subjects Total

S1 Face-area, left 7 Hand-area, right – Face-area, right – S2 Medial/posterior, left – Lateral/anterior, left 5 Medial/posterior, right – Lateral/anterior, right 5 Insular cortex Anterior, left – Medial, left 5 Posterior, left 4 Anterior, right 8 Medial, right 5 Posterior, right – Anterior cingulate cortex (ACC) Anterior, left 4 Posterior, left 8 Posterior, right 7 Precentral gyrus Face-area, left 3 Hand-area, right 4 Face-area, right 5 Orbital gyrus Left 6 Right 6 Inferior frontal gyrus Left 5 Right 7 Medial frontal gyrus Left 6 Right 8 Superior frontal gyrus Left 7 Right 7

Group analysis t-values

P-values

W

S

W

S

C

2 – –

7 – –

5.04 – –

8.22 – –

– 1 – 1

– 4 – 5

– 5.84 – 5.59

– 9.09 – 8.98

– 2 1 6 1 –

– 4 4 3 5 –

– 4.33 3.98 2.45 2.50 –

– 6.94 6.39 2.44 5.82 –

–

1 5 3

3 5 5

1.97 1.53 2.87

1 3 1

3 1 5

3 3

W

Talairach coordinates x

y

z

0.0003 – –

K57 – –

K9 – –

22 – –

– !0.0001 – !0.0001

– – !0.0001 0.0002 – – !0.0001 0.0001

– K55 – 55

– K9 – K2

– 16 – 14

– !0.0001 0.0001 0.0146 0.0126 –

– – !0.0001 0.0027 !0.0001 0.0054 0.0150 0.9935 !0.0001 0.0001 – –

– K35 K36 40 40 –

–

3.01 2.79 0.01 3.81

2 K11 8 0 –

– 9 15 4 7 –

3.78 3.14 0.51

2.09 1.85 K2.67

0.0492 0.1253 0.0042

0.0372 0.0653 0.0077

K3 K1 10

33 2 2

25 38 34

2.98 3.90 4.10

5.85 7.07 7.73

3.30 3.65 4.18

0.0029 !0.0001 0.0010 0.0001 !0.0001 0.0003 !0.0001 !0.0001 !0.0001

K57 51 48

1 K6 K9

18 40 17

3 4

3.17 3.35

2.04 2.20

K1.27 K1.30

3 5

2 3

2.28 3.72

4.06 5.54

3 7

3 2

3.42 7.40

4 5

6 3

7.34 4.48

3.66 – – – 3.76 – 3.91 –

S

C

!0.0001 !0.0001 – – – –

0.0016 0.0008

0.0002 0.0017 0.6074

0.0412 0.0283

0.2041 0.1936

K20 25

49 41

1 2

2.05 2.10

0.0229 0.0001 0.0002 !0.0001

0.0410 0.0358

K38 54

31 23

1 10

0.93 4.40

K2.83 K3.38

0.0006 0.3523 !0.0001 !0.0001

0.0048 0.0008

K35 37

49 44

18 21

4.20 1.28

K3.55 K3.63

!0.0001 !0.0001 !0.0001 0.2018

0.0004 0.0003

K24 21

56 52

33 18

Results of the single subject and group analysis of the TWS experiment in the different brain regions. The columns ‘number of subjects’ show the number of subjects in whom activation was found by the single subject analysis. The numbers are given separately for both stimuli (total), weak tooth pain (W) and strong tooth pain (S). The next columns show the t-values and their P-values as obtained by the general linear model (GLM), which was used for the group analysis. Again, they are given separately for weak tooth pain (W), strong tooth pain (S) and for the contrast (C). Positive t-values for contrasts represent higher BOLD changes during strong tooth stimulation as compared with weak stimulation and vice versa for negative t-values. All significant t-values are printed in bold. The Talairach coordinate denote the center of gravity of the cluster as found by the group analysis.

reflex vasodilatation that the trigeminal innervation in the mouth does not cross the midline (Kemppainen et al., 2003). Our findings are in line with earlier reported features of the trigeminal cortical representation. For example, experimental data from primates reported that S1 (Cusick et al., 1986; Lin et al., 1993) and motor cortical neurons (Lemon, 1981; Martin et al., 1999) responded to tactile stimulation of ipsilateral and bilateral receptive fields in the face. In contrast, the limb S1 (Asanuma and Arissian, 1984; Iwamura and Tanaka, 1991) and motor cortical areas (Lemon and Porter, 1976; Murphy et al., 1978) received almost exclusively contralateral input. It has been shown

consistently that bilateral lesions (Larson et al., 1980) and suppression of the neuronal activity in face S1 (Lin et al., 1993) and motor cortex (Murray et al., 1991) by bilateral cooling markedly impaired tongue and jaw motor function, whereas unilateral suppression had no marked effect. Clinical findings in patients have confirmed that unilateral cortical infarctions (covering both hand and face M1 and S1 regions), while causing serious impairment of upper limb function on the contralateral side, do not impair bite force and jaw-closing function (Kemppainen et al., 1999). S2 and the insular region, in contrast to S1, are known to receive bilateral input from the limbs and from the

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Change of BOLD signal (%)

1.2

S2 ipsi, lateral part

0.8 0.4 0 -0.4

0

80

160 240 time (sec)

320

400

resting period weak tooth pain strong tooth pain

Fig. 5. Time course of BOLD-signals in the ipsilateral S2 area during the TWS experiment. The courses of the signals were subdivided into 19 segments, each lasting 21 s. The mean value of these segments were used to calculated the BOLD changes shown in this plot.

trigeminus (Dong et al., 1989; Robinson and Burton, 1980). In S2, we found a clear somatotopy. The centers of gravity of the hand activation were more medial/posterior; the respective centers of tooth pain more lateral/anterior (Craig, 2002). The S2 fields predominantly activated by tooth input showed also clear intensity coding of the tooth pulp stimulus. The insula has been regarded belonging to the ‘lateral’ and ‘medial’ pain projection system (Craig, 2004; Treede et al., 1999). Anterior, medial, and posterior parts of the left insular cortex were stronger activated by tooth compared to hand stimulation, in the right insular cortex this was observed only in the medial part. The posterior right insular cortex was clearly more activated by hand stimulation. This distribution was also reflected in the TWS experiment: The medial and posterior parts of the left insular cortex, but only the medial right insula, showed intensity coding of the tooth stimulation. Our results on hand pain are to some degree in agreement with an earlier study by Craig et al. (2000) and by Peyron et al. (2002) which showed that ipsilateral activation was more rostral than the contralateral one. In the present study, we found a clear dominance of the tooth over hand representation in the whole left (ipsilateral) insula and in the right medial insula. According to Craig (2003, 2004), the insular cortex processes mainly ‘interoceptive’ pain perception. The posterior insula is supposed to be also involved in thermal perception (Hua et al., 2005). This notion is supported by our finding that tooth pain, a kind of visceral pain, plays a dominant role in most parts of the left insula. Our results in the contralateral (right) insula confirm a previous study demonstrating some degree of anterior– posterior somatotopy in the contralateral insula (Brooks et al., 2005). Surprisingly, in the HT experiment there was no significant activation of the perigenual part of the anterior cingulate cortex (ACC) by either hand or tooth stimulation which was demonstrated at least for hand stimulation in other studies (Buchel et al., 2002; Kupers et al., 2004; Mohr

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et al., 2005). In the posterior ACC hand pain induced significantly stronger cortical activations. In the TWS experiment, the left perigenual ACC was activated only by the strong tooth stimulus. The ACC is subdivided based on function, neuronal projections and cytoarchitecture (Bush et al., 2000; Devinsky et al., 1995). The anterior part (perigenual cingulate) has been associated with emotional or affective reactions. Apparently, only the strong tooth stimuli during the TWS experiment were effectively engaging the affective pain dimension and caused activation in this region. The posterior division of ACC (midcingulate) is supposed to be involved in more ‘cognitive’ tasks (Bantick et al., 2002; Mohr et al., 2005). Here, we found antagonistic responses: In the ipsilateral field they were larger during the stronger tooth stimuli, in the contralateral homologuous field it was the other way around. This region sends projections to the lateral prefrontal cortex and to motor areas and has been identified as part of an extended ‘attentional’ cortical network (Devinsky et al., 1995; Mohr et al., 2005). The inverse intensity coding in the contralateral (right) midcingulate region is of particular interest in the light of the projections of this area to the frontal cortex since inverse intensity coding of tooth pain was there also encountered. In most of the frontal cortical regions, tooth pain had a greater impact compared to hand stimulation with the notable exception of the orbital and the left superior frontal gyrus. Frontal cortical areas get input from the midcingulate, but also from other limbic structures and from the insula (Bantick et al., 2002). It has been shown that electrical stimulation of the orbitofrontal and medial prefrontal cortices results in analgesia (Oleson et al., 1980; Thorpe et al., 1983). The orbital frontal cortex did not reveal a clear coding of tooth pain in the TWS experiment and the medial and superior frontal gyri of both hemispheres showed a clear inverse coding. This is in agreement with previous studies, which also described a negative correlation between experimental pain intensity ratings and activation of frontal areas (Bantick et al., 2002; Derbyshire et al., 1997). Inverse coding, i.e. stronger responses to weaker pain stimuli, can be brought together with a role of the respective areas in the cognitive and emotional assessment of the tooth pain stimuli. Dominance and intensity coding of tooth pain was surprisingly found in the motor areas (precentral gyrus) of both hemispheres not only in the projection area of the face but also in the hand area. Since, we have parceled out rating related activations by using the rating movements as a covariate in the GLM model, this result cannot be attributed to the rating task which had also to be performed during hand stimulation. Therefore, the activations in these areas reflect perhaps the focusing of attention on the input which probably was a more demanding task in case of the ‘interoceptive’ tooth pulp input compared to the input from mechanical hand stimulation.

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5. Conclusions It is concluded that tooth pain activates a cortical network which is in some respects different from that of hand pain, not only in the somatotopically organized S1 and S2 fields, but also in parts of the ‘medial’ pain projection system. Most conspicuous are the generally stronger activations in frontal areas where inverse coding of tooth pain intensity was found at several sites.

Acknowledgements This work was supported by the Deutsche Forschungsgemeinschaft, SFB 353, the DAAD, and the Academy of Finland.

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